Point Cloud Library (PCL)  1.8.1-dev
Namespaces | Classes | Typedefs | Enumerations | Functions | Variables
pcl Namespace Reference

Namespaces

 common
 
 ComparisonOps
 
 console
 
 cuda
 
 detail
 
 device
 
 distances
 
 face_detection
 
 features
 
 fields
 
 filters
 
 geometry
 
 gpu
 
 io
 
 ism
 
 keypoints
 
 kinfuLS
 
 ndt2d
 
 occlusion_reasoning
 
 octree
 
 outofcore
 
 people
 
 poisson
 
 recognition
 
 registration
 
 search
 
 segmentation
 
 surface
 
 test
 test_macros.h provide helper macros for testing vectors, matrices etc.
 
 texture_mapping
 
 tracking
 
 traits
 
 utils
 
 visualization
 

Classes

struct  PointXYZIEdge
 This typedef is used to represent a point cloud containing edge information. More...
 
class  Convolution
 A 2D convolution class. More...
 
class  Edge
 
class  kernel
 
class  Keypoint
 Keypoint represents the base class for key points. More...
 
class  Morphology
 
class  CloudIterator
 Iterator class for point clouds with or without given indices. More...
 
class  ConstCloudIterator
 Iterator class for point clouds with or without given indices. More...
 
class  BivariatePolynomialT
 This represents a bivariate polynomial and provides some functionality for it. More...
 
struct  NdCentroidFunctor
 Helper functor structure for n-D centroid estimation. More...
 
class  CentroidPoint
 A generic class that computes the centroid of points fed to it. More...
 
class  GlasbeyLUT
 Color lookup table consisting of 256 colors structured in a maximally discontinuous manner. More...
 
struct  NdConcatenateFunctor
 Helper functor structure for concatenate. More...
 
class  FeatureHistogram
 Type for histograms for computing mean and variance of some floats. More...
 
class  GaussianKernel
 Class GaussianKernel assembles all the method for computing, convolving, smoothing, gradients computing an image using a gaussian kernel. More...
 
class  PCA
 Principal Component analysis (PCA) class. More...
 
class  PiecewiseLinearFunction
 This provides functionalities to efficiently return values for piecewise linear function. More...
 
class  PolynomialCalculationsT
 This provides some functionality for polynomials, like finding roots or approximating bivariate polynomials. More...
 
class  PosesFromMatches
 calculate 3D transformation based on point correspondencdes More...
 
class  PointCloud
 PointCloud represents the base class in PCL for storing collections of 3D points. More...
 
class  Synchronizer
 /brief This template class synchronizes two data streams of different types. More...
 
class  StopWatch
 Simple stopwatch. More...
 
class  ScopeTime
 Class to measure the time spent in a scope. More...
 
class  EventFrequency
 A helper class to measure frequency of a certain event. More...
 
class  TimeTrigger
 Timer class that invokes registered callback methods periodically. More...
 
class  TransformationFromCorrespondences
 Calculates a transformation based on corresponding 3D points. More...
 
class  VectorAverage
 Calculates the weighted average and the covariance matrix. More...
 
struct  Correspondence
 Correspondence represents a match between two entities (e.g., points, descriptors, etc). More...
 
struct  PointCorrespondence3D
 Representation of a (possible) correspondence between two 3D points in two different coordinate frames (e.g. More...
 
struct  PointCorrespondence6D
 Representation of a (possible) correspondence between two points (e.g. More...
 
class  PCLException
 A base class for all pcl exceptions which inherits from std::runtime_error. More...
 
class  InvalidConversionException
 An exception that is thrown when a PCLPointCloud2 message cannot be converted into a PCL type. More...
 
class  IsNotDenseException
 An exception that is thrown when a PointCloud is not dense but is attemped to be used as dense. More...
 
class  InvalidSACModelTypeException
 An exception that is thrown when a sample consensus model doesn't have the correct number of samples defined in model_types.h. More...
 
class  IOException
 An exception that is thrown during an IO error (typical read/write errors) More...
 
class  InitFailedException
 An exception thrown when init can not be performed should be used in all the PCLBase class inheritants. More...
 
class  UnorganizedPointCloudException
 An exception that is thrown when an organized point cloud is needed but not provided. More...
 
class  KernelWidthTooSmallException
 An exception that is thrown when the kernel size is too small. More...
 
class  UnhandledPointTypeException
 
class  ComputeFailedException
 
class  BadArgumentException
 An exception that is thrown when the argments number or type is wrong/unhandled. More...
 
struct  for_each_type_impl
 
struct  for_each_type_impl< false >
 
struct  intersect
 
class  DefaultIterator
 
class  IteratorIdx
 
struct  _PointXYZ
 
struct  PointXYZ
 A point structure representing Euclidean xyz coordinates. More...
 
struct  _RGB
 
struct  RGB
 A structure representing RGB color information. More...
 
struct  _Intensity
 
struct  Intensity
 A point structure representing the grayscale intensity in single-channel images. More...
 
struct  _Intensity8u
 
struct  Intensity8u
 A point structure representing the grayscale intensity in single-channel images. More...
 
struct  _Intensity32u
 
struct  Intensity32u
 A point structure representing the grayscale intensity in single-channel images. More...
 
struct  _PointXYZI
 A point structure representing Euclidean xyz coordinates, and the intensity value. More...
 
struct  PointXYZI
 
struct  _PointXYZL
 
struct  PointXYZL
 
struct  Label
 
struct  _PointXYZRGBA
 
struct  PointXYZRGBA
 A point structure representing Euclidean xyz coordinates, and the RGBA color. More...
 
struct  _PointXYZRGB
 
struct  _PointXYZRGBL
 
struct  PointXYZRGB
 A point structure representing Euclidean xyz coordinates, and the RGB color. More...
 
struct  PointXYZRGBL
 
struct  _PointXYZHSV
 
struct  PointXYZHSV
 
struct  PointXY
 A 2D point structure representing Euclidean xy coordinates. More...
 
struct  PointUV
 A 2D point structure representing pixel image coordinates. More...
 
struct  InterestPoint
 A point structure representing an interest point with Euclidean xyz coordinates, and an interest value. More...
 
struct  _Normal
 
struct  Normal
 A point structure representing normal coordinates and the surface curvature estimate. More...
 
struct  _Axis
 
struct  Axis
 A point structure representing an Axis using its normal coordinates. More...
 
struct  _PointNormal
 
struct  PointNormal
 A point structure representing Euclidean xyz coordinates, together with normal coordinates and the surface curvature estimate. More...
 
struct  _PointXYZRGBNormal
 
struct  PointXYZRGBNormal
 A point structure representing Euclidean xyz coordinates, and the RGB color, together with normal coordinates and the surface curvature estimate. More...
 
struct  _PointXYZINormal
 
struct  PointXYZINormal
 A point structure representing Euclidean xyz coordinates, intensity, together with normal coordinates and the surface curvature estimate. More...
 
struct  _PointXYZLNormal
 
struct  PointXYZLNormal
 A point structure representing Euclidean xyz coordinates, a label, together with normal coordinates and the surface curvature estimate. More...
 
struct  _PointWithRange
 
struct  PointWithRange
 A point structure representing Euclidean xyz coordinates, padded with an extra range float. More...
 
struct  _PointWithViewpoint
 
struct  PointWithViewpoint
 A point structure representing Euclidean xyz coordinates together with the viewpoint from which it was seen. More...
 
struct  MomentInvariants
 A point structure representing the three moment invariants. More...
 
struct  PrincipalRadiiRSD
 A point structure representing the minimum and maximum surface radii (in meters) computed using RSD. More...
 
struct  Boundary
 A point structure representing a description of whether a point is lying on a surface boundary or not. More...
 
struct  PrincipalCurvatures
 A point structure representing the principal curvatures and their magnitudes. More...
 
struct  PFHSignature125
 A point structure representing the Point Feature Histogram (PFH). More...
 
struct  PFHRGBSignature250
 A point structure representing the Point Feature Histogram with colors (PFHRGB). More...
 
struct  PPFSignature
 A point structure for storing the Point Pair Feature (PPF) values. More...
 
struct  CPPFSignature
 A point structure for storing the Point Pair Feature (CPPF) values. More...
 
struct  PPFRGBSignature
 A point structure for storing the Point Pair Color Feature (PPFRGB) values. More...
 
struct  NormalBasedSignature12
 A point structure representing the Normal Based Signature for a feature matrix of 4-by-3. More...
 
struct  ShapeContext1980
 A point structure representing a Shape Context. More...
 
struct  UniqueShapeContext1960
 A point structure representing a Unique Shape Context. More...
 
struct  SHOT352
 A point structure representing the generic Signature of Histograms of OrienTations (SHOT) - shape only. More...
 
struct  SHOT1344
 A point structure representing the generic Signature of Histograms of OrienTations (SHOT) - shape+color. More...
 
struct  _ReferenceFrame
 A structure representing the Local Reference Frame of a point. More...
 
struct  ReferenceFrame
 
struct  FPFHSignature33
 A point structure representing the Fast Point Feature Histogram (FPFH). More...
 
struct  VFHSignature308
 A point structure representing the Viewpoint Feature Histogram (VFH). More...
 
struct  GRSDSignature21
 A point structure representing the Global Radius-based Surface Descriptor (GRSD). More...
 
struct  BRISKSignature512
 A point structure representing the Binary Robust Invariant Scalable Keypoints (BRISK). More...
 
struct  ESFSignature640
 A point structure representing the Ensemble of Shape Functions (ESF). More...
 
struct  GFPFHSignature16
 A point structure representing the GFPFH descriptor with 16 bins. More...
 
struct  Narf36
 A point structure representing the Narf descriptor. More...
 
struct  BorderDescription
 A structure to store if a point in a range image lies on a border between an obstacle and the background. More...
 
struct  IntensityGradient
 A point structure representing the intensity gradient of an XYZI point cloud. More...
 
struct  Histogram
 A point structure representing an N-D histogram. More...
 
struct  _PointWithScale
 
struct  PointWithScale
 A point structure representing a 3-D position and scale. More...
 
struct  _PointSurfel
 
struct  PointSurfel
 A surfel, that is, a point structure representing Euclidean xyz coordinates, together with normal coordinates, a RGBA color, a radius, a confidence value and the surface curvature estimate. More...
 
struct  _PointDEM
 
struct  PointDEM
 A point structure representing Digital Elevation Map. More...
 
struct  ModelCoefficients
 
class  PCLBase
 PCL base class. More...
 
class  PCLBase< pcl::PCLPointCloud2 >
 
struct  PCLHeader
 
struct  PCLImage
 
struct  PCLPointCloud2
 
struct  PCLPointField
 
struct  NdCopyEigenPointFunctor
 Helper functor structure for copying data between an Eigen type and a PointT. More...
 
struct  NdCopyPointEigenFunctor
 Helper functor structure for copying data between an Eigen type and a PointT. More...
 
class  PointRepresentation
 PointRepresentation provides a set of methods for converting a point structs/object into an n-dimensional vector. More...
 
class  DefaultPointRepresentation
 DefaultPointRepresentation extends PointRepresentation to define default behavior for common point types. More...
 
class  DefaultFeatureRepresentation
 DefaulFeatureRepresentation extends PointRepresentation and is intended to be used when defining the default behavior for feature descriptor types (i.e., copy each element of each field into a float array). More...
 
class  DefaultPointRepresentation< PointXYZ >
 
class  DefaultPointRepresentation< PointXYZI >
 
class  DefaultPointRepresentation< PointNormal >
 
class  DefaultPointRepresentation< PFHSignature125 >
 
class  DefaultPointRepresentation< PFHRGBSignature250 >
 
class  DefaultPointRepresentation< PPFSignature >
 
class  DefaultPointRepresentation< FPFHSignature33 >
 
class  DefaultPointRepresentation< VFHSignature308 >
 
class  DefaultPointRepresentation< Narf36 >
 
class  DefaultPointRepresentation< NormalBasedSignature12 >
 
class  DefaultPointRepresentation< ShapeContext1980 >
 
class  DefaultPointRepresentation< UniqueShapeContext1960 >
 
class  DefaultPointRepresentation< SHOT352 >
 
class  DefaultPointRepresentation< SHOT1344 >
 
class  CustomPointRepresentation
 CustomPointRepresentation extends PointRepresentation to allow for sub-part selection on the point. More...
 
struct  FieldMatches
 
struct  CopyIfFieldExists
 A helper functor that can copy a specific value if the given field exists. More...
 
struct  SetIfFieldExists
 A helper functor that can set a specific value in a field if the field exists. More...
 
struct  PointIndices
 
struct  PolygonMesh
 
class  BearingAngleImage
 class BearingAngleImage is used as an interface to generate Bearing Angle(BA) image. More...
 
class  RangeImage
 RangeImage is derived from pcl/PointCloud and provides functionalities with focus on situations where a 3D scene was captured from a specific view point. More...
 
class  RangeImagePlanar
 RangeImagePlanar is derived from the original range image and differs from it because it's not a spherical projection, but using a projection plane (as normal cameras do), therefore being better applicable for range sensors that already provide a range image by themselves (stereo cameras, ToF-cameras), so that a conversion to point cloud and then to a spherical range image becomes unnecessary. More...
 
class  RangeImageSpherical
 RangeImageSpherical is derived from the original range image and uses a slightly different spherical projection. More...
 
struct  TexMaterial
 
struct  TextureMesh
 
struct  Vertices
 Describes a set of vertices in a polygon mesh, by basically storing an array of indices. More...
 
class  OrganizedNeighborSearch
 OrganizedNeighborSearch class More...
 
class  ShapeContext3DEstimation
 ShapeContext3DEstimation implements the 3D shape context descriptor as described in: More...
 
class  BOARDLocalReferenceFrameEstimation
 BOARDLocalReferenceFrameEstimation implements the BOrder Aware Repeatable Directions algorithm for local reference frame estimation as described here: More...
 
class  BoundaryEstimation
 BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle criterion. More...
 
class  BRISK2DEstimation
 Implementation of the BRISK-descriptor, based on the original code and paper reference by. More...
 
class  CPPFEstimation
 Class that calculates the "surflet" features for each pair in the given pointcloud. More...
 
class  CRHEstimation
 CRHEstimation estimates the Camera Roll Histogram (CRH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: More...
 
class  CVFHEstimation
 CVFHEstimation estimates the Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: More...
 
class  DifferenceOfNormalsEstimation
 A Difference of Normals (DoN) scale filter implementation for point cloud data. More...
 
class  ESFEstimation
 ESFEstimation estimates the ensemble of shape functions descriptors for a given point cloud dataset containing points. More...
 
class  Feature
 Feature represents the base feature class. More...
 
class  FeatureFromNormals
 
class  FeatureFromLabels
 
class  FeatureWithLocalReferenceFrames
 FeatureWithLocalReferenceFrames provides a public interface for descriptor extractor classes which need a local reference frame at each input keypoint. More...
 
class  FPFHEstimation
 FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals. More...
 
class  FPFHEstimationOMP
 FPFHEstimationOMP estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals, in parallel, using the OpenMP standard. More...
 
class  GFPFHEstimation
 GFPFHEstimation estimates the Global Fast Point Feature Histogram (GFPFH) descriptor for a given point cloud dataset containing points and labels. More...
 
class  GRSDEstimation
 GRSDEstimation estimates the Global Radius-based Surface Descriptor (GRSD) for a given point cloud dataset containing points and normals. More...
 
struct  IntegralImageTypeTraits
 
struct  IntegralImageTypeTraits< float >
 
struct  IntegralImageTypeTraits< char >
 
struct  IntegralImageTypeTraits< short >
 
struct  IntegralImageTypeTraits< unsigned short >
 
struct  IntegralImageTypeTraits< unsigned char >
 
struct  IntegralImageTypeTraits< int >
 
struct  IntegralImageTypeTraits< unsigned int >
 
class  IntegralImage2D
 Determines an integral image representation for a given organized data array. More...
 
class  IntegralImage2D< DataType, 1 >
 partial template specialization for integral images with just one channel. More...
 
class  IntegralImageNormalEstimation
 Surface normal estimation on organized data using integral images. More...
 
class  IntensityGradientEstimation
 IntensityGradientEstimation estimates the intensity gradient for a point cloud that contains position and intensity values. More...
 
class  IntensitySpinEstimation
 IntensitySpinEstimation estimates the intensity-domain spin image descriptors for a given point cloud dataset containing points and intensity. More...
 
class  LinearLeastSquaresNormalEstimation
 Surface normal estimation on dense data using a least-squares estimation based on a first-order Taylor approximation. More...
 
class  MomentInvariantsEstimation
 MomentInvariantsEstimation estimates the 3 moment invariants (j1, j2, j3) at each 3D point. More...
 
class  MomentOfInertiaEstimation
 Implements the method for extracting features based on moment of inertia. More...
 
class  MultiscaleFeaturePersistence
 Generic class for extracting the persistent features from an input point cloud It can be given any Feature estimator instance and will compute the features of the input over a multiscale representation of the cloud and output the unique ones over those scales. More...
 
class  Narf
 NARF (Normal Aligned Radial Features) is a point feature descriptor type for 3D data. More...
 
class  NarfDescriptor
 Computes NARF feature descriptors for points in a range image See B. More...
 
class  NormalEstimation
 NormalEstimation estimates local surface properties (surface normals and curvatures)at each 3D point. More...
 
class  NormalEstimationOMP
 NormalEstimationOMP estimates local surface properties at each 3D point, such as surface normals and curvatures, in parallel, using the OpenMP standard. More...
 
class  NormalBasedSignatureEstimation
 Normal-based feature signature estimation class. More...
 
class  OrganizedEdgeBase
 OrganizedEdgeBase, OrganizedEdgeFromRGB, OrganizedEdgeFromNormals, and OrganizedEdgeFromRGBNormals find 3D edges from an organized point cloud data. More...
 
class  OrganizedEdgeFromRGB
 
class  OrganizedEdgeFromNormals
 
class  OrganizedEdgeFromRGBNormals
 
class  OURCVFHEstimation
 OURCVFHEstimation estimates the Oriented, Unique and Repetable Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset given XYZ data and normals, as presented in: More...
 
class  PFHEstimation
 PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals. More...
 
class  PFHRGBEstimation
 
class  PPFEstimation
 Class that calculates the "surflet" features for each pair in the given pointcloud. More...
 
class  PPFRGBEstimation
 
class  PPFRGBRegionEstimation
 
class  PrincipalCurvaturesEstimation
 PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals. More...
 
class  RangeImageBorderExtractor
 Extract obstacle borders from range images, meaning positions where there is a transition from foreground to background. More...
 
class  RIFTEstimation
 RIFTEstimation estimates the Rotation Invariant Feature Transform descriptors for a given point cloud dataset containing points and intensity. More...
 
class  ROPSEstimation
 This class implements the method for extracting RoPS features presented in the article "Rotational Projection Statistics for 3D Local Surface Description and Object Recognition" by Yulan Guo, Ferdous Sohel, Mohammed Bennamoun, Min Lu and Jianwei Wan. More...
 
class  RSDEstimation
 RSDEstimation estimates the Radius-based Surface Descriptor (minimal and maximal radius of the local surface's curves) for a given point cloud dataset containing points and normals. More...
 
class  SHOTEstimationBase
 SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals. More...
 
class  SHOTEstimation
 SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals. More...
 
class  SHOTColorEstimation
 SHOTColorEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points, normals and colors. More...
 
class  SHOTLocalReferenceFrameEstimation
 SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor. More...
 
class  SHOTLocalReferenceFrameEstimationOMP
 SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor. More...
 
class  SHOTEstimationOMP
 SHOTEstimationOMP estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals, in parallel, using the OpenMP standard. More...
 
class  SHOTColorEstimationOMP
 SHOTColorEstimationOMP estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points, normals and colors, in parallel, using the OpenMP standard. More...
 
class  SpinImageEstimation
 Estimates spin-image descriptors in the given input points. More...
 
class  StatisticalMultiscaleInterestRegionExtraction
 Class for extracting interest regions from unstructured point clouds, based on a multi scale statistical approach. More...
 
class  UniqueShapeContext
 UniqueShapeContext implements the Unique Shape Context Descriptor described here: More...
 
class  VFHEstimation
 VFHEstimation estimates the Viewpoint Feature Histogram (VFH) descriptor for a given point cloud dataset containing points and normals. More...
 
struct  xNdCopyEigenPointFunctor
 Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More...
 
struct  xNdCopyPointEigenFunctor
 Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More...
 
class  ApproximateVoxelGrid
 ApproximateVoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
 
class  BilateralFilter
 A bilateral filter implementation for point cloud data. More...
 
class  BoxClipper3D
 Implementation of a box clipper in 3D. Actually it allows affine transformations, thus any parallelepiped in general pose. The affine transformation is used to transform the point before clipping it using the unit cube centered at origin and with an extend of -1 to +1 in each dimension. More...
 
class  Clipper3D
 Base class for 3D clipper objects. More...
 
class  PointDataAtOffset
 A datatype that enables type-correct comparisons. More...
 
class  ComparisonBase
 The (abstract) base class for the comparison object. More...
 
class  FieldComparison
 The field-based specialization of the comparison object. More...
 
class  PackedRGBComparison
 A packed rgb specialization of the comparison object. More...
 
class  PackedHSIComparison
 A packed HSI specialization of the comparison object. More...
 
class  TfQuadraticXYZComparison
 A comparison whether the (x,y,z) components of a given point satisfy (p'Ap + 2v'p + c [OP] 0). More...
 
class  ConditionBase
 Base condition class. More...
 
class  ConditionAnd
 AND condition. More...
 
class  ConditionOr
 OR condition. More...
 
class  ConditionalRemoval
 ConditionalRemoval filters data that satisfies certain conditions. More...
 
class  CovarianceSampling
 Point Cloud sampling based on the 6D covariances. More...
 
class  CropBox
 CropBox is a filter that allows the user to filter all the data inside of a given box. More...
 
class  CropBox< pcl::PCLPointCloud2 >
 CropBox is a filter that allows the user to filter all the data inside of a given box. More...
 
class  CropHull
 Filter points that lie inside or outside a 3D closed surface or 2D closed polygon, as generated by the ConvexHull or ConcaveHull classes. More...
 
class  ExtractIndices
 ExtractIndices extracts a set of indices from a point cloud. More...
 
class  ExtractIndices< pcl::PCLPointCloud2 >
 ExtractIndices extracts a set of indices from a point cloud. More...
 
class  FastBilateralFilter
 Implementation of a fast bilateral filter for smoothing depth information in organized point clouds Based on the following paper: More...
 
class  FastBilateralFilterOMP
 Implementation of a fast bilateral filter for smoothing depth information in organized point clouds Based on the following paper: More...
 
class  Filter
 Filter represents the base filter class. More...
 
class  Filter< pcl::PCLPointCloud2 >
 Filter represents the base filter class. More...
 
class  FilterIndices
 FilterIndices represents the base class for filters that are about binary point removal. More...
 
class  FilterIndices< pcl::PCLPointCloud2 >
 FilterIndices represents the base class for filters that are about binary point removal. More...
 
class  FrustumCulling
 FrustumCulling filters points inside a frustum given by pose and field of view of the camera. More...
 
class  GridMinimum
 GridMinimum assembles a local 2D grid over a given PointCloud, and downsamples the data. More...
 
class  LocalMaximum
 LocalMaximum downsamples the cloud, by eliminating points that are locally maximal. More...
 
class  MedianFilter
 Implementation of the median filter. More...
 
class  ModelOutlierRemoval
 ModelOutlierRemoval filters points in a cloud based on the distance between model and point. More...
 
class  NormalRefinement
 Normal vector refinement class More...
 
class  NormalSpaceSampling
 NormalSpaceSampling samples the input point cloud in the space of normal directions computed at every point. More...
 
class  PassThrough
 PassThrough passes points in a cloud based on constraints for one particular field of the point type. More...
 
class  PassThrough< pcl::PCLPointCloud2 >
 PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints. More...
 
class  PlaneClipper3D
 Implementation of a plane clipper in 3D. More...
 
class  ProjectInliers
 ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More...
 
class  ProjectInliers< pcl::PCLPointCloud2 >
 ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More...
 
class  RadiusOutlierRemoval
 RadiusOutlierRemoval filters points in a cloud based on the number of neighbors they have. More...
 
class  RadiusOutlierRemoval< pcl::PCLPointCloud2 >
 RadiusOutlierRemoval is a simple filter that removes outliers if the number of neighbors in a certain search radius is smaller than a given K. More...
 
class  RandomSample
 RandomSample applies a random sampling with uniform probability. More...
 
class  RandomSample< pcl::PCLPointCloud2 >
 RandomSample applies a random sampling with uniform probability. More...
 
class  SamplingSurfaceNormal
 SamplingSurfaceNormal divides the input space into grids until each grid contains a maximum of N points, and samples points randomly within each grid. More...
 
class  ShadowPoints
 ShadowPoints removes the ghost points appearing on edge discontinuties More...
 
class  StatisticalOutlierRemoval
 StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More...
 
class  StatisticalOutlierRemoval< pcl::PCLPointCloud2 >
 StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More...
 
class  UniformSampling
 UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
 
class  VoxelGrid
 VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
 
class  VoxelGrid< pcl::PCLPointCloud2 >
 VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
 
class  VoxelGridCovariance
 A searchable voxel strucure containing the mean and covariance of the data. More...
 
class  VoxelGridLabel
 
class  VoxelGridOcclusionEstimation
 VoxelGrid to estimate occluded space in the scene. More...
 
class  LineIterator
 Organized Index Iterator for iterating over the "pixels" for a given line using the Bresenham algorithm. More...
 
class  OrganizedIndexIterator
 base class for iterators on 2-dimensional maps like images/organized clouds etc. More...
 
class  PlanarPolygon
 PlanarPolygon represents a planar (2D) polygon, potentially in a 3D space. More...
 
class  TSDFVolume
 
class  AdaptiveRangeCoder
 AdaptiveRangeCoder compression class More...
 
class  StaticRangeCoder
 StaticRangeCoder compression class More...
 
class  ASCIIReader
 Ascii Point Cloud Reader. More...
 
class  DavidSDKGrabber
 Grabber for davidSDK structured light compliant devices. More...
 
class  DepthSenseGrabber
 Grabber for DepthSense devices (e.g. More...
 
class  DinastGrabber
 Grabber for DINAST devices (i.e., IPA-1002, IPA-1110, IPA-2001) More...
 
class  EnsensoGrabber
 Grabber for IDS-Imaging Ensenso's devices. More...
 
class  FileGrabber
 FileGrabber provides a container-style interface for grabbers which operate on fixed-size input. More...
 
class  FileReader
 Point Cloud Data (FILE) file format reader interface. More...
 
class  FileWriter
 Point Cloud Data (FILE) file format writer. More...
 
class  Grabber
 Grabber interface for PCL 1.x device drivers. More...
 
class  HDLGrabber
 Grabber for the Velodyne High-Definition-Laser (HDL) More...
 
class  IFSReader
 Indexed Face set (IFS) file format reader. More...
 
class  IFSWriter
 Point Cloud Data (IFS) file format writer. More...
 
class  ImageGrabberBase
 Base class for Image file grabber. More...
 
class  ImageGrabber
 
class  SynchronizedQueue
 
class  MTLReader
 
class  OBJReader
 
class  ONIGrabber
 A simple ONI grabber. More...
 
class  OpenNIGrabber
 Grabber for OpenNI devices (i.e., Primesense PSDK, Microsoft Kinect, Asus XTion Pro/Live) More...
 
class  PCDGrabberBase
 Base class for PCD file grabber. More...
 
class  PCDGrabber
 
class  PCDReader
 Point Cloud Data (PCD) file format reader. More...
 
class  PCDWriter
 Point Cloud Data (PCD) file format writer. More...
 
class  PLYReader
 Point Cloud Data (PLY) file format reader. More...
 
class  PLYWriter
 Point Cloud Data (PLY) file format writer. More...
 
class  RealSenseGrabber
 
class  RobotEyeGrabber
 Grabber for the Ocular Robotics RobotEye sensor. More...
 
class  VLPGrabber
 Grabber for the Velodyne LiDAR (VLP), based on the Velodyne High Definition Laser (HDL) More...
 
class  KdTree
 KdTree represents the base spatial locator class for kd-tree implementations. More...
 
class  KdTreeFLANN
 KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. More...
 
class  AgastKeypoint2DBase
 Detects 2D AGAST corner points. More...
 
class  AgastKeypoint2D
 Detects 2D AGAST corner points. More...
 
class  AgastKeypoint2D< pcl::PointXYZ, pcl::PointUV >
 Detects 2D AGAST corner points. More...
 
class  BriskKeypoint2D
 Detects BRISK interest points based on the original code and paper reference by. More...
 
class  HarrisKeypoint2D
 HarrisKeypoint2D detects Harris corners family points. More...
 
class  HarrisKeypoint3D
 HarrisKeypoint3D uses the idea of 2D Harris keypoints, but instead of using image gradients, it uses surface normals. More...
 
class  HarrisKeypoint6D
 Keypoint detector for detecting corners in 3D (XYZ), 2D (intensity) AND mixed versions of these. More...
 
class  ISSKeypoint3D
 ISSKeypoint3D detects the Intrinsic Shape Signatures keypoints for a given point cloud. More...
 
class  NarfKeypoint
 NARF (Normal Aligned Radial Feature) keypoints. More...
 
struct  SIFTKeypointFieldSelector
 
struct  SIFTKeypointFieldSelector< PointNormal >
 
struct  SIFTKeypointFieldSelector< PointXYZRGB >
 
struct  SIFTKeypointFieldSelector< PointXYZRGBA >
 
class  SIFTKeypoint
 SIFTKeypoint detects the Scale Invariant Feature Transform keypoints for a given point cloud dataset containing points and intensity. More...
 
class  SmoothedSurfacesKeypoint
 Based on the paper: Xinju Li and Igor Guskov Multi-scale features for approximate alignment of point-based surfaces Proceedings of the third Eurographics symposium on Geometry processing July 2005, Vienna, Austria. More...
 
class  SUSANKeypoint
 SUSANKeypoint implements a RGB-D extension of the SUSAN detector inluding normal directions variation in top of intensity variation. More...
 
class  TrajkovicKeypoint2D
 TrajkovicKeypoint2D implements Trajkovic and Hedley corner detector on organized pooint cloud using intensity information. More...
 
class  TrajkovicKeypoint3D
 TrajkovicKeypoint3D implements Trajkovic and Hedley corner detector on point cloud using geometric information. More...
 
class  BranchEstimator
 Interface for branch estimators. More...
 
class  BinaryTreeThresholdBasedBranchEstimator
 Branch estimator for binary trees where the branch is computed only from the threshold. More...
 
class  TernaryTreeMissingDataBranchEstimator
 Branch estimator for ternary trees where one branch is used for missing data (indicated by flag != 0). More...
 
class  DenseCrf
 
class  DecisionForest
 Class representing a decision forest. More...
 
class  DecisionForestEvaluator
 Utility class for evaluating a decision forests. More...
 
class  DecisionForestTrainer
 Trainer for decision trees. More...
 
class  DecisionTree
 Class representing a decision tree. More...
 
class  DecisionTreeTrainerDataProvider
 
class  DecisionTreeEvaluator
 Utility class for evaluating a decision tree. More...
 
class  DecisionTreeTrainer
 Trainer for decision trees. More...
 
class  FeatureHandler
 Utility class interface which is used for creating and evaluating features. More...
 
class  Fern
 Class representing a Fern. More...
 
class  FernEvaluator
 Utility class for evaluating a fern. More...
 
class  FernTrainer
 Trainer for a Fern. More...
 
class  Kmeans
 K-means clustering. More...
 
class  MultiChannel2DComparisonFeature
 Feature for comparing two sample points in 2D multi-channel data. More...
 
class  MultiChannel2DComparisonFeatureHandler
 Feature utility class that handles the creation and evaluation of RGBD comparison features. More...
 
class  ScaledMultiChannel2DComparisonFeatureHandler
 Feature utility class that handles the creation and evaluation of RGBD comparison features. More...
 
class  ScaledMultiChannel2DComparisonFeatureHandlerCCodeGenerator
 
class  MultiChannel2DData
 Holds two-dimensional multi-channel data. More...
 
class  MultiChannel2DDataSet
 Holds a set of two-dimensional multi-channel data. More...
 
struct  MultipleData2DExampleIndex
 Example index for a set of 2D data blocks. More...
 
class  PairwisePotential
 
class  Permutohedral
 Implementation of a high-dimensional gaussian filtering using the permutohedral lattice. More...
 
class  HashTableOLD
 
class  PointXY32f
 2D point with float x- and y-coordinates. More...
 
class  PointXY32i
 2D point with integer x- and y-coordinates. More...
 
class  RegressionVarianceNode
 Node for a regression trees which optimizes variance. More...
 
class  RegressionVarianceStatsEstimator
 Statistics estimator for regression trees which optimizes variance. More...
 
class  StatsEstimator
 Class interface for gathering statistics for decision tree learning. More...
 
struct  SVMParam
 The structure stores the parameters for the classificationa nd must be initialized and passed to the training method pcl::SVMTrain. More...
 
struct  SVMModel
 The structure initialize a model crated by the SVM (Support Vector Machines) classifier (pcl::SVMTrain) More...
 
struct  SVMDataPoint
 The structure initialize a single feature value for the classification using SVM (Support Vector Machines). More...
 
struct  SVMData
 The structure stores the features and the label of a single sample which has to be used for the training or the classification of the SVM (Support Vector Machines). More...
 
class  SVM
 Base class for SVM SVM (Support Vector Machines). More...
 
class  SVMTrain
 SVM (Support Vector Machines) training class for the SVM machine learning. More...
 
class  SVMClassify
 SVM (Support Vector Machines) classification of a dataset. More...
 
class  CorrespondenceGrouping
 Abstract base class for Correspondence Grouping algorithms. More...
 
class  GeometricConsistencyGrouping
 Class implementing a 3D correspondence grouping enforcing geometric consistency among feature correspondences. More...
 
class  Hough3DGrouping
 Class implementing a 3D correspondence grouping algorithm that can deal with multiple instances of a model template found into a given scene. More...
 
class  ColorGradientDOTModality
 
class  ColorGradientModality
 Modality based on max-RGB gradients. More...
 
class  ColorModality
 
class  CRHAlignment
 CRHAlignment uses two Camera Roll Histograms (CRH) to find the roll rotation that aligns both views. More...
 
struct  DenseQuantizedSingleModTemplate
 
struct  DenseQuantizedMultiModTemplate
 
class  DistanceMap
 Represents a distance map obtained from a distance transformation. More...
 
class  DOTModality
 
struct  DOTMODDetection
 
class  DOTMOD
 Template matching using the DOTMOD approach. More...
 
class  RFFaceDetectorTrainer
 
class  GreedyVerification
 A greedy hypothesis verification method. More...
 
class  GlobalHypothesesVerification
 A hypothesis verification method proposed in "A Global Hypotheses Verification Method for 3D Object Recognition", A. More...
 
class  PapazovHV
 A hypothesis verification method proposed in "An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes", C. More...
 
class  HypothesisVerification
 Abstract class for hypotheses verification methods. More...
 
struct  ISMPeak
 This struct is used for storing peak. More...
 
struct  BoundingBoxXYZ
 
class  LineRGBD
 High-level class for template matching using the LINEMOD approach based on RGB and Depth data. More...
 
class  EnergyMaps
 Stores a set of energy maps. More...
 
class  LinearizedMaps
 Stores a set of linearized maps. More...
 
struct  LINEMODDetection
 Represents a detection of a template using the LINEMOD approach. More...
 
class  LINEMOD
 Template matching using the LINEMOD approach. More...
 
class  MaskMap
 
struct  GradientXY
 A point structure representing Euclidean xyz coordinates, and the intensity value. More...
 
class  QuantizableModality
 Interface for a quantizable modality. More...
 
class  QuantizedMap
 
struct  RegionXY
 Defines a region in XY-space. More...
 
struct  QuantizedMultiModFeature
 Feature that defines a position and quantized value in a specific modality. More...
 
struct  SparseQuantizedMultiModTemplate
 A multi-modality template constructed from a set of quantized multi-modality features. More...
 
struct  LINEMOD_OrientationMap
 Map that stores orientations. More...
 
struct  QuantizedNormalLookUpTable
 Look-up-table for fast surface normal quantization. More...
 
class  SurfaceNormalModality
 Modality based on surface normals. More...
 
class  SolverDidntConvergeException
 An exception that is thrown when the non linear solver didn't converge. More...
 
class  NotEnoughPointsException
 An exception that is thrown when the number of correspondants is not equal to the minimum required. More...
 
class  GeneralizedIterativeClosestPoint
 GeneralizedIterativeClosestPoint is an ICP variant that implements the generalized iterative closest point algorithm as described by Alex Segal et al. More...
 
struct  _PointXYZLAB
 
struct  PointXYZLAB
 A custom point type for position and CIELAB color value. More...
 
class  GraphRegistration
 GraphRegistration class is the base class for graph-based registration methods More...
 
class  SampleConsensusInitialAlignment
 SampleConsensusInitialAlignment is an implementation of the initial alignment algorithm described in section IV of "Fast Point Feature Histograms (FPFH) for 3D Registration," Rusu et al. More...
 
class  IterativeClosestPoint
 IterativeClosestPoint provides a base implementation of the Iterative Closest Point algorithm. More...
 
class  IterativeClosestPointWithNormals
 IterativeClosestPointWithNormals is a special case of IterativeClosestPoint, that uses a transformation estimated based on Point to Plane distances by default. More...
 
class  IterativeClosestPointNonLinear
 IterativeClosestPointNonLinear is an ICP variant that uses Levenberg-Marquardt optimization backend. More...
 
class  JointIterativeClosestPoint
 JointIterativeClosestPoint extends ICP to multiple frames which share the same transform. More...
 
class  NormalDistributionsTransform
 A 3D Normal Distribution Transform registration implementation for point cloud data. More...
 
class  NormalDistributionsTransform2D
 NormalDistributionsTransform2D provides an implementation of the Normal Distributions Transform algorithm for scan matching. More...
 
class  PairwiseGraphRegistration
 PairwiseGraphRegistration class aligns the clouds two by two More...
 
class  PPFHashMapSearch
 
class  PPFRegistration
 Class that registers two point clouds based on their sets of PPFSignatures. More...
 
class  PyramidFeatureHistogram
 Class that compares two sets of features by using a multiscale representation of the features inside a pyramid. More...
 
class  Registration
 Registration represents the base registration class for general purpose, ICP-like methods. More...
 
class  SampleConsensusPrerejective
 Pose estimation and alignment class using a prerejective RANSAC routine. More...
 
class  LeastMedianSquares
 LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm. More...
 
class  MaximumLikelihoodSampleConsensus
 MaximumLikelihoodSampleConsensus represents an implementation of the MLESAC (Maximum Likelihood Estimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S. More...
 
class  MEstimatorSampleConsensus
 MEstimatorSampleConsensus represents an implementation of the MSAC (M-estimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S. More...
 
class  ProgressiveSampleConsensus
 RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm, as described in: "Matching with PROSAC – Progressive Sample Consensus", Chum, O. More...
 
class  RandomSampleConsensus
 RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm, as described in: "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography", Martin A. More...
 
class  RandomizedMEstimatorSampleConsensus
 RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized M-estimator SAmple Consensus) algorithm, which basically adds a Td,d test (see RandomizedRandomSampleConsensus) to an MSAC estimator (see MEstimatorSampleConsensus). More...
 
class  RandomizedRandomSampleConsensus
 RandomizedRandomSampleConsensus represents an implementation of the RRANSAC (Randomized RAndom SAmple Consensus), as described in "Randomized RANSAC with Td,d test", O. More...
 
class  SampleConsensus
 SampleConsensus represents the base class. More...
 
class  SampleConsensusModel
 SampleConsensusModel represents the base model class. More...
 
class  SampleConsensusModelFromNormals
 SampleConsensusModelFromNormals represents the base model class for models that require the use of surface normals for estimation. More...
 
struct  Functor
 Base functor all the models that need non linear optimization must define their own one and implement operator() (const Eigen::VectorXd& x, Eigen::VectorXd& fvec) or operator() (const Eigen::VectorXf& x, Eigen::VectorXf& fvec) dependening on the choosen _Scalar. More...
 
class  SampleConsensusModelCircle2D
 SampleConsensusModelCircle2D defines a model for 2D circle segmentation on the X-Y plane. More...
 
class  SampleConsensusModelCircle3D
 SampleConsensusModelCircle3D defines a model for 3D circle segmentation. More...
 
class  SampleConsensusModelCone
 SampleConsensusModelCone defines a model for 3D cone segmentation. More...
 
class  SampleConsensusModelCylinder
 SampleConsensusModelCylinder defines a model for 3D cylinder segmentation. More...
 
class  SampleConsensusModelLine
 SampleConsensusModelLine defines a model for 3D line segmentation. More...
 
class  SampleConsensusModelNormalParallelPlane
 SampleConsensusModelNormalParallelPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...
 
class  SampleConsensusModelNormalPlane
 SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...
 
class  SampleConsensusModelNormalSphere
 SampleConsensusModelNormalSphere defines a model for 3D sphere segmentation using additional surface normal constraints. More...
 
class  SampleConsensusModelParallelLine
 SampleConsensusModelParallelLine defines a model for 3D line segmentation using additional angular constraints. More...
 
class  SampleConsensusModelParallelPlane
 SampleConsensusModelParallelPlane defines a model for 3D plane segmentation using additional angular constraints. More...
 
class  SampleConsensusModelPerpendicularPlane
 SampleConsensusModelPerpendicularPlane defines a model for 3D plane segmentation using additional angular constraints. More...
 
class  SampleConsensusModelPlane
 SampleConsensusModelPlane defines a model for 3D plane segmentation. More...
 
class  SampleConsensusModelRegistration
 SampleConsensusModelRegistration defines a model for Point-To-Point registration outlier rejection. More...
 
class  SampleConsensusModelRegistration2D
 SampleConsensusModelRegistration2D defines a model for Point-To-Point registration outlier rejection using distances between 2D pixels. More...
 
class  SampleConsensusModelSphere
 SampleConsensusModelSphere defines a model for 3D sphere segmentation. More...
 
class  SampleConsensusModelStick
 SampleConsensusModelStick defines a model for 3D stick segmentation. More...
 
class  ApproximateProgressiveMorphologicalFilter
 Implements the Progressive Morphological Filter for segmentation of ground points. More...
 
class  Comparator
 Comparator is the base class for comparators that compare two points given some function. More...
 
class  ConditionalEuclideanClustering
 ConditionalEuclideanClustering performs segmentation based on Euclidean distance and a user-defined clustering condition. More...
 
class  CPCSegmentation
 A segmentation algorithm partitioning a supervoxel graph. More...
 
class  CrfNormalSegmentation
 
class  CrfSegmentation
 
class  EdgeAwarePlaneComparator
 EdgeAwarePlaneComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
 
class  EuclideanClusterComparator
 EuclideanClusterComparator is a comparator used for finding clusters supported by planar surfaces. More...
 
class  EuclideanPlaneCoefficientComparator
 EuclideanPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
 
class  EuclideanClusterExtraction
 EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense. More...
 
class  LabeledEuclideanClusterExtraction
 LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, with label info. More...
 
class  ExtractPolygonalPrismData
 ExtractPolygonalPrismData uses a set of point indices that represent a planar model, and together with a given height, generates a 3D polygonal prism. More...
 
class  GrabCut
 Implementation of the GrabCut segmentation in "GrabCut — Interactive Foreground Extraction using Iterated Graph Cuts" by Carsten Rother, Vladimir Kolmogorov and Andrew Blake. More...
 
class  GroundPlaneComparator
 GroundPlaneComparator is a Comparator for detecting smooth surfaces suitable for driving. More...
 
class  LCCPSegmentation
 A simple segmentation algorithm partitioning a supervoxel graph into groups of locally convex connected supervoxels separated by concave borders. More...
 
class  OrganizedConnectedComponentSegmentation
 OrganizedConnectedComponentSegmentation allows connected components to be found within organized point cloud data, given a comparison function. More...
 
class  OrganizedMultiPlaneSegmentation
 OrganizedMultiPlaneSegmentation finds all planes present in the input cloud, and outputs a vector of plane equations, as well as a vector of point clouds corresponding to the inliers of each detected plane. More...
 
class  PlanarPolygonFusion
 PlanarPolygonFusion takes a list of 2D planar polygons and attempts to reduce them to a minimum set that best represents the scene, based on various given comparators. More...
 
class  PlanarRegion
 PlanarRegion represents a set of points that lie in a plane. More...
 
class  PlaneCoefficientComparator
 PlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
 
class  PlaneRefinementComparator
 PlaneRefinementComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
 
class  ProgressiveMorphologicalFilter
 Implements the Progressive Morphological Filter for segmentation of ground points. More...
 
class  Region3D
 Region3D represents summary statistics of a 3D collection of points. More...
 
class  RegionGrowing
 Implements the well known Region Growing algorithm used for segmentation. More...
 
class  RegionGrowingRGB
 Implements the well known Region Growing algorithm used for segmentation based on color of points. More...
 
class  RGBPlaneCoefficientComparator
 RGBPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
 
class  SACSegmentation
 SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models, in the sense that it just creates a Nodelet wrapper for generic-purpose SAC-based segmentation. More...
 
class  SACSegmentationFromNormals
 SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation. More...
 
class  SeededHueSegmentation
 SeededHueSegmentation. More...
 
class  SegmentDifferences
 SegmentDifferences obtains the difference between two spatially aligned point clouds and returns the difference between them for a maximum given distance threshold. More...
 
class  Supervoxel
 Supervoxel container class - stores a cluster extracted using supervoxel clustering. More...
 
class  SupervoxelClustering
 Implements a supervoxel algorithm based on voxel structure, normals, and rgb values. More...
 
class  UnaryClassifier
 
class  DigitalElevationMapBuilder
 Build a Digital Elevation Map in the column-disparity space from a disparity map and a color image of the scene. More...
 
class  DisparityMapConverter
 Compute point cloud from the disparity map. More...
 
class  StereoGrabberBase
 Base class for Stereo file grabber. More...
 
class  StereoGrabber
 
class  StereoMatching
 Stereo Matching abstract class. More...
 
class  GrayStereoMatching
 Stereo Matching abstract class for Grayscale images. More...
 
class  BlockBasedStereoMatching
 Block based (or fixed window) Stereo Matching class. More...
 
class  AdaptiveCostSOStereoMatching
 Adaptive Cost 2-pass Scanline Optimization Stereo Matching class. More...
 
class  BilateralUpsampling
 Bilateral filtering implementation, based on the following paper: More...
 
class  ConcaveHull
 ConcaveHull (alpha shapes) using libqhull library. More...
 
class  ConvexHull
 ConvexHull using libqhull library. More...
 
class  EarClipping
 The ear clipping triangulation algorithm. More...
 
class  GreedyProjectionTriangulation
 GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections. More...
 
class  GridProjection
 Grid projection surface reconstruction method. More...
 
class  MarchingCubes
 The marching cubes surface reconstruction algorithm. More...
 
class  MarchingCubesHoppe
 The marching cubes surface reconstruction algorithm, using a signed distance function based on the distance from tangent planes, proposed by Hoppe et. More...
 
class  MarchingCubesRBF
 The marching cubes surface reconstruction algorithm, using a signed distance function based on radial basis functions. More...
 
struct  MLSResult
 Data structure used to store the results of the MLS fitting. More...
 
class  MovingLeastSquares
 MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation. More...
 
class  OrganizedFastMesh
 Simple triangulation/surface reconstruction for organized point clouds. More...
 
class  Poisson
 The Poisson surface reconstruction algorithm. More...
 
class  CloudSurfaceProcessing
 CloudSurfaceProcessing represents the base class for algorithms that takes a point cloud as input and produces a new output cloud that has been modified towards a better surface representation. More...
 
class  MeshProcessing
 MeshProcessing represents the base class for mesh processing algorithms. More...
 
class  PCLSurfaceBase
 Pure abstract class. More...
 
class  SurfaceReconstruction
 SurfaceReconstruction represents a base surface reconstruction class. More...
 
class  MeshConstruction
 MeshConstruction represents a base surface reconstruction class. More...
 
class  SurfelSmoothing
 
class  TextureMapping
 The texture mapping algorithm. More...
 
class  MeshQuadricDecimationVTK
 PCL mesh decimation based on vtkQuadricDecimation from the VTK library. More...
 
class  MeshSmoothingLaplacianVTK
 PCL mesh smoothing based on the vtkSmoothPolyDataFilter algorithm from the VTK library. More...
 
class  MeshSmoothingWindowedSincVTK
 PCL mesh smoothing based on the vtkWindowedSincPolyDataFilter algorithm from the VTK library. More...
 
class  MeshSubdivisionVTK
 PCL mesh smoothing based on the vtkLinearSubdivisionFilter, vtkLoopSubdivisionFilter, vtkButterflySubdivisionFilter depending on the selected MeshSubdivisionVTKFilterType algorithm from the VTK library. More...
 
class  VTKUtils
 
class  RegistrationVisualizer
 RegistrationVisualizer represents the base class for rendering the intermediate positions occupied by the source point cloud during it's registration to the target point cloud. More...
 

Typedefs

typedef BivariatePolynomialT
< double > 
BivariatePolynomiald
 
typedef BivariatePolynomialT
< float > 
BivariatePolynomial
 
typedef
PolynomialCalculationsT
< double > 
PolynomialCalculationsd
 
typedef
PolynomialCalculationsT< float > 
PolynomialCalculations
 
typedef VectorAverage< float, 2 > VectorAverage2f
 
typedef VectorAverage< float, 3 > VectorAverage3f
 
typedef VectorAverage< float, 4 > VectorAverage4f
 
typedef std::vector
< pcl::Correspondence,
Eigen::aligned_allocator
< pcl::Correspondence > > 
Correspondences
 
typedef boost::shared_ptr
< Correspondences
CorrespondencesPtr
 
typedef boost::shared_ptr
< const Correspondences
CorrespondencesConstPtr
 
typedef std::vector
< PointCorrespondence3D,
Eigen::aligned_allocator
< PointCorrespondence3D > > 
PointCorrespondences3DVector
 
typedef std::vector
< PointCorrespondence6D,
Eigen::aligned_allocator
< PointCorrespondence6D > > 
PointCorrespondences6DVector
 
typedef Eigen::Map
< Eigen::Array3f > 
Array3fMap
 
typedef const Eigen::Map
< const Eigen::Array3f > 
Array3fMapConst
 
typedef Eigen::Map
< Eigen::Array4f,
Eigen::Aligned > 
Array4fMap
 
typedef const Eigen::Map
< const Eigen::Array4f,
Eigen::Aligned > 
Array4fMapConst
 
typedef Eigen::Map
< Eigen::Vector3f > 
Vector3fMap
 
typedef const Eigen::Map
< const Eigen::Vector3f > 
Vector3fMapConst
 
typedef Eigen::Map
< Eigen::Vector4f,
Eigen::Aligned > 
Vector4fMap
 
typedef const Eigen::Map
< const Eigen::Vector4f,
Eigen::Aligned > 
Vector4fMapConst
 
typedef Eigen::Matrix< uint8_t, 3, 1 > Vector3c
 
typedef Eigen::Map< Vector3cVector3cMap
 
typedef const Eigen::Map
< const Vector3c
Vector3cMapConst
 
typedef Eigen::Matrix< uint8_t, 4, 1 > Vector4c
 
typedef Eigen::Map< Vector4c,
Eigen::Aligned > 
Vector4cMap
 
typedef const Eigen::Map
< const Vector4c,
Eigen::Aligned > 
Vector4cMapConst
 
typedef boost::shared_ptr
< ::pcl::ModelCoefficients
ModelCoefficientsPtr
 
typedef boost::shared_ptr
< ::pcl::ModelCoefficients
const > 
ModelCoefficientsConstPtr
 
typedef boost::shared_ptr
< std::vector< int > > 
IndicesPtr
 
typedef boost::shared_ptr
< const std::vector< int > > 
IndicesConstPtr
 
typedef boost::shared_ptr
< PCLHeader
HeaderPtr
 
typedef boost::shared_ptr
< PCLHeader const > 
HeaderConstPtr
 
typedef boost::shared_ptr
< ::pcl::PCLImage
PCLImagePtr
 
typedef boost::shared_ptr
< ::pcl::PCLImage const > 
PCLImageConstPtr
 
typedef boost::shared_ptr
< ::pcl::PCLPointCloud2
PCLPointCloud2Ptr
 
typedef boost::shared_ptr
< ::pcl::PCLPointCloud2 const > 
PCLPointCloud2ConstPtr
 
typedef boost::shared_ptr
< ::pcl::PCLPointField
PCLPointFieldPtr
 
typedef boost::shared_ptr
< ::pcl::PCLPointField const > 
PCLPointFieldConstPtr
 
typedef std::vector
< detail::FieldMapping
MsgFieldMap
 
typedef std::bitset< 32 > BorderTraits
 Data type to store extended information about a transition from foreground to backgroundSpecification of the fields for BorderDescription::traits. More...
 
typedef boost::shared_ptr
< ::pcl::PointIndices
PointIndicesPtr
 
typedef boost::shared_ptr
< ::pcl::PointIndices const > 
PointIndicesConstPtr
 
typedef boost::shared_ptr
< ::pcl::PolygonMesh
PolygonMeshPtr
 
typedef boost::shared_ptr
< ::pcl::PolygonMesh const > 
PolygonMeshConstPtr
 
typedef boost::shared_ptr
< pcl::TextureMesh
TextureMeshPtr
 
typedef boost::shared_ptr
< pcl::TextureMesh const > 
TextureMeshConstPtr
 
typedef boost::shared_ptr
< Vertices
VerticesPtr
 
typedef boost::shared_ptr
< Vertices const > 
VerticesConstPtr
 
typedef
MultiChannel2DComparisonFeatureHandler
< float, 1 > 
Depth2DComparisonFeatureHandler
 
typedef
MultiChannel2DComparisonFeatureHandler
< float, 2 > 
IntensityDepth2DComparisonFeatureHandler
 
typedef
MultiChannel2DComparisonFeatureHandler
< float, 3 > 
RGB2DComparisonFeatureHandler
 
typedef
MultiChannel2DComparisonFeatureHandler
< float, 4 > 
RGBD2DComparisonFeatureHandler
 
typedef
ScaledMultiChannel2DComparisonFeatureHandler
< float, 1, 0, true > 
ScaledDepth2DComparisonFeatureHandler
 
typedef
ScaledMultiChannel2DComparisonFeatureHandler
< float, 2, 1, true > 
ScaledIntensityDepth2DComparisonFeatureHandler
 
typedef
ScaledMultiChannel2DComparisonFeatureHandler
< float, 4, 3, true > 
ScaledRGBD2DComparisonFeatureHandler
 
typedef
ScaledMultiChannel2DComparisonFeatureHandlerCCodeGenerator
< float, 1, 0, true > 
ScaledDepth2DComparisonFeatureHandlerCCodeGenerator
 
typedef MultiChannel2DDataSet
< float, 1 > 
Depth2DDataSet
 
typedef MultiChannel2DDataSet
< float, 2 > 
IntensityDepth2DDataSet
 
typedef MultiChannel2DDataSet
< float, 3 > 
RGB2DDataSet
 
typedef MultiChannel2DDataSet
< float, 4 > 
RGBD2DDataSet
 
typedef std::vector
< pcl::PointIndices
IndicesClusters
 
typedef boost::shared_ptr
< std::vector
< pcl::PointIndices > > 
IndicesClustersPtr
 

Enumerations

enum  InterpolationType {
  BORDER_CONSTANT = 0, BORDER_REPLICATE = 1, BORDER_REFLECT = 2, BORDER_WRAP = 3,
  BORDER_REFLECT_101 = 4, BORDER_TRANSPARENT = 5, BORDER_DEFAULT = BORDER_REFLECT_101
}
 
enum  NormType {
  L1, L2_SQR, L2, LINF,
  JM, B, SUBLINEAR, CS,
  DIV, PF, K, KL,
  HIK
}
 Enum that defines all the types of norms available. More...
 
enum  BorderTrait {
  BORDER_TRAIT__OBSTACLE_BORDER, BORDER_TRAIT__SHADOW_BORDER, BORDER_TRAIT__VEIL_POINT, BORDER_TRAIT__SHADOW_BORDER_TOP,
  BORDER_TRAIT__SHADOW_BORDER_RIGHT, BORDER_TRAIT__SHADOW_BORDER_BOTTOM, BORDER_TRAIT__SHADOW_BORDER_LEFT, BORDER_TRAIT__OBSTACLE_BORDER_TOP,
  BORDER_TRAIT__OBSTACLE_BORDER_RIGHT, BORDER_TRAIT__OBSTACLE_BORDER_BOTTOM, BORDER_TRAIT__OBSTACLE_BORDER_LEFT, BORDER_TRAIT__VEIL_POINT_TOP,
  BORDER_TRAIT__VEIL_POINT_RIGHT, BORDER_TRAIT__VEIL_POINT_BOTTOM, BORDER_TRAIT__VEIL_POINT_LEFT
}
 Specification of the fields for BorderDescription::traits. More...
 
enum  MorphologicalOperators { MORPH_OPEN, MORPH_CLOSE, MORPH_DILATE, MORPH_ERODE }
 
enum  SacModel {
  SACMODEL_PLANE, SACMODEL_LINE, SACMODEL_CIRCLE2D, SACMODEL_CIRCLE3D,
  SACMODEL_SPHERE, SACMODEL_CYLINDER, SACMODEL_CONE, SACMODEL_TORUS,
  SACMODEL_PARALLEL_LINE, SACMODEL_PERPENDICULAR_PLANE, SACMODEL_PARALLEL_LINES, SACMODEL_NORMAL_PLANE,
  SACMODEL_NORMAL_SPHERE, SACMODEL_REGISTRATION, SACMODEL_REGISTRATION_2D, SACMODEL_PARALLEL_PLANE,
  SACMODEL_NORMAL_PARALLEL_PLANE, SACMODEL_STICK
}
 

Functions

float rad2deg (float alpha)
 Convert an angle from radians to degrees. More...
 
float deg2rad (float alpha)
 Convert an angle from degrees to radians. More...
 
double rad2deg (double alpha)
 Convert an angle from radians to degrees. More...
 
double deg2rad (double alpha)
 Convert an angle from degrees to radians. More...
 
float normAngle (float alpha)
 Normalize an angle to (-PI, PI]. More...
 
template<typename real >
std::ostream & operator<< (std::ostream &os, const BivariatePolynomialT< real > &p)
 
template<typename PointT , typename Scalar >
unsigned int compute3DCentroid (ConstCloudIterator< PointT > &cloud_iterator, Eigen::Matrix< Scalar, 4, 1 > &centroid)
 Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector. More...
 
template<typename PointT >
unsigned int compute3DCentroid (ConstCloudIterator< PointT > &cloud_iterator, Eigen::Vector4f &centroid)
 
template<typename PointT >
unsigned int compute3DCentroid (ConstCloudIterator< PointT > &cloud_iterator, Eigen::Vector4d &centroid)
 
template<typename PointT , typename Scalar >
unsigned int compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 4, 1 > &centroid)
 Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector. More...
 
template<typename PointT >
unsigned int compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &centroid)
 
template<typename PointT >
unsigned int compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4d &centroid)
 
template<typename PointT , typename Scalar >
unsigned int compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix< Scalar, 4, 1 > &centroid)
 Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector. More...
 
template<typename PointT >
unsigned int compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Vector4f &centroid)
 
template<typename PointT >
unsigned int compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Vector4d &centroid)
 
template<typename PointT , typename Scalar >
unsigned int compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, 4, 1 > &centroid)
 Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector. More...
 
template<typename PointT >
unsigned int compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4f &centroid)
 
template<typename PointT >
unsigned int compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4d &centroid)
 
template<typename PointT , typename Scalar >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
 Compute the 3x3 covariance matrix of a given set of points. More...
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
 
template<typename PointT , typename Scalar >
unsigned int computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
 Compute normalized the 3x3 covariance matrix of a given set of points. More...
 
template<typename PointT >
unsigned int computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 
template<typename PointT >
unsigned int computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
 
template<typename PointT , typename Scalar >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
 Compute the 3x3 covariance matrix of a given set of points using their indices. More...
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
 
template<typename PointT , typename Scalar >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
 Compute the 3x3 covariance matrix of a given set of points using their indices. More...
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
 
template<typename PointT , typename Scalar >
unsigned int computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
 Compute the normalized 3x3 covariance matrix of a given set of points using their indices. More...
 
template<typename PointT >
unsigned int computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 
template<typename PointT >
unsigned int computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
 
template<typename PointT , typename Scalar >
unsigned int computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
 Compute the normalized 3x3 covariance matrix of a given set of points using their indices. More...
 
template<typename PointT >
unsigned int computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 
template<typename PointT >
unsigned int computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4d &centroid, Eigen::Matrix3d &covariance_matrix)
 
template<typename PointT , typename Scalar >
unsigned int computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > &centroid)
 Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. More...
 
template<typename PointT >
unsigned int computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f &centroid)
 
template<typename PointT >
unsigned int computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d &centroid)
 
template<typename PointT , typename Scalar >
unsigned int computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > &centroid)
 Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. More...
 
template<typename PointT >
unsigned int computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f &centroid)
 
template<typename PointT >
unsigned int computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d &centroid)
 
template<typename PointT , typename Scalar >
unsigned int computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix, Eigen::Matrix< Scalar, 4, 1 > &centroid)
 Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop. More...
 
template<typename PointT >
unsigned int computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f &centroid)
 
template<typename PointT >
unsigned int computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d &centroid)
 
template<typename PointT , typename Scalar >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
 Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. More...
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3f &covariance_matrix)
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3d &covariance_matrix)
 
template<typename PointT , typename Scalar >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
 Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. More...
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix3f &covariance_matrix)
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix3d &covariance_matrix)
 
template<typename PointT , typename Scalar >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, 3, 3 > &covariance_matrix)
 Compute the normalized 3x3 covariance matrix for a already demeaned point cloud. More...
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3f &covariance_matrix)
 
template<typename PointT >
unsigned int computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3d &covariance_matrix)
 
template<typename PointT , typename Scalar >
void demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Matrix< Scalar, 4, 1 > &centroid, pcl::PointCloud< PointT > &cloud_out, int npts=0)
 Subtract a centroid from a point cloud and return the de-meaned representation. More...
 
template<typename PointT >
void demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4f &centroid, pcl::PointCloud< PointT > &cloud_out, int npts=0)
 
template<typename PointT >
void demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4d &centroid, pcl::PointCloud< PointT > &cloud_out, int npts=0)
 
template<typename PointT , typename Scalar >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Matrix< Scalar, 4, 1 > &centroid, pcl::PointCloud< PointT > &cloud_out)
 Subtract a centroid from a point cloud and return the de-meaned representation. More...
 
template<typename PointT >
void demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4f &centroid, pcl::PointCloud< PointT > &cloud_out)
 
template<typename PointT >
void demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4d &centroid, pcl::PointCloud< PointT > &cloud_out)
 
template<typename PointT , typename Scalar >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, pcl::PointCloud< PointT > &cloud_out)
 Subtract a centroid from a point cloud and return the de-meaned representation. More...
 
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, const Eigen::Vector4f &centroid, pcl::PointCloud< PointT > &cloud_out)
 
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, const Eigen::Vector4d &centroid, pcl::PointCloud< PointT > &cloud_out)
 
template<typename PointT , typename Scalar >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, pcl::PointCloud< PointT > &cloud_out)
 Subtract a centroid from a point cloud and return the de-meaned representation. More...
 
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4f &centroid, pcl::PointCloud< PointT > &cloud_out)
 
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4d &centroid, pcl::PointCloud< PointT > &cloud_out)
 
template<typename PointT , typename Scalar >
void demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out, int npts=0)
 Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
 
template<typename PointT >
void demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4f &centroid, Eigen::MatrixXf &cloud_out, int npts=0)
 
template<typename PointT >
void demeanPointCloud (ConstCloudIterator< PointT > &cloud_iterator, const Eigen::Vector4d &centroid, Eigen::MatrixXd &cloud_out, int npts=0)
 
template<typename PointT , typename Scalar >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out)
 Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
 
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Vector4f &centroid, Eigen::MatrixXf &cloud_out)
 
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Vector4d &centroid, Eigen::MatrixXd &cloud_out)
 
template<typename PointT , typename Scalar >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out)
 Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
 
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, const Eigen::Vector4f &centroid, Eigen::MatrixXf &cloud_out)
 
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, const Eigen::Vector4d &centroid, Eigen::MatrixXd &cloud_out)
 
template<typename PointT , typename Scalar >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Matrix< Scalar, 4, 1 > &centroid, Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > &cloud_out)
 Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix. More...
 
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4f &centroid, Eigen::MatrixXf &cloud_out)
 
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, const Eigen::Vector4d &centroid, Eigen::MatrixXd &cloud_out)
 
template<typename PointT , typename Scalar >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &centroid)
 General, all purpose nD centroid estimation for a set of points using their indices. More...
 
template<typename PointT >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::VectorXf &centroid)
 
template<typename PointT >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::VectorXd &centroid)
 
template<typename PointT , typename Scalar >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &centroid)
 General, all purpose nD centroid estimation for a set of points using their indices. More...
 
template<typename PointT >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::VectorXf &centroid)
 
template<typename PointT >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::VectorXd &centroid)
 
template<typename PointT , typename Scalar >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &centroid)
 General, all purpose nD centroid estimation for a set of points using their indices. More...
 
template<typename PointT >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::VectorXf &centroid)
 
template<typename PointT >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::VectorXd &centroid)
 
template<typename PointInT , typename PointOutT >
size_t computeCentroid (const pcl::PointCloud< PointInT > &cloud, PointOutT &centroid)
 Compute the centroid of a set of points and return it as a point. More...
 
template<typename PointInT , typename PointOutT >
size_t computeCentroid (const pcl::PointCloud< PointInT > &cloud, const std::vector< int > &indices, PointOutT &centroid)
 Compute the centroid of a set of points and return it as a point. More...
 
PCL_EXPORTS RGB getRandomColor (double min=0.2, double max=2.8)
 
double getAngle3D (const Eigen::Vector4f &v1, const Eigen::Vector4f &v2, const bool in_degree=false)
 Compute the smallest angle between two 3D vectors in radians (default) or degree. More...
 
double getAngle3D (const Eigen::Vector3f &v1, const Eigen::Vector3f &v2, const bool in_degree=false)
 Compute the smallest angle between two 3D vectors in radians (default) or degree. More...
 
void getMeanStd (const std::vector< float > &values, double &mean, double &stddev)
 Compute both the mean and the standard deviation of an array of values. More...
 
template<typename PointT >
void getPointsInBox (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, std::vector< int > &indices)
 Get a set of points residing in a box given its bounds. More...
 
template<typename PointT >
void getMaxDistance (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f &pivot_pt, Eigen::Vector4f &max_pt)
 Get the point at maximum distance from a given point and a given pointcloud. More...
 
template<typename PointT >
void getMaxDistance (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Vector4f &pivot_pt, Eigen::Vector4f &max_pt)
 Get the point at maximum distance from a given point and a given pointcloud. More...
 
template<typename PointT >
void getMinMax3D (const pcl::PointCloud< PointT > &cloud, PointT &min_pt, PointT &max_pt)
 Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. More...
 
template<typename PointT >
void getMinMax3D (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt)
 Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. More...
 
template<typename PointT >
void getMinMax3D (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt)
 Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. More...
 
template<typename PointT >
void getMinMax3D (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt)
 Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud. More...
 
template<typename PointT >
double getCircumcircleRadius (const PointT &pa, const PointT &pb, const PointT &pc)
 Compute the radius of a circumscribed circle for a triangle formed of three points pa, pb, and pc. More...
 
template<typename PointT >
void getMinMax (const PointT &histogram, int len, float &min_p, float &max_p)
 Get the minimum and maximum values on a point histogram. More...
 
template<typename PointT >
float calculatePolygonArea (const pcl::PointCloud< PointT > &polygon)
 Calculate the area of a polygon given a point cloud that defines the polygon. More...
 
PCL_EXPORTS void getMinMax (const pcl::PCLPointCloud2 &cloud, int idx, const std::string &field_name, float &min_p, float &max_p)
 Get the minimum and maximum values on a point histogram. More...
 
PCL_EXPORTS void getMeanStdDev (const std::vector< float > &values, double &mean, double &stddev)
 Compute both the mean and the standard deviation of an array of values. More...
 
template<typename PointInT , typename PointOutT >
void copyPoint (const PointInT &point_in, PointOutT &point_out)
 Copy the fields of a source point into a target point. More...
 
PCL_EXPORTS void lineToLineSegment (const Eigen::VectorXf &line_a, const Eigen::VectorXf &line_b, Eigen::Vector4f &pt1_seg, Eigen::Vector4f &pt2_seg)
 Get the shortest 3D segment between two 3D lines. More...
 
double sqrPointToLineDistance (const Eigen::Vector4f &pt, const Eigen::Vector4f &line_pt, const Eigen::Vector4f &line_dir)
 Get the square distance from a point to a line (represented by a point and a direction) More...
 
double sqrPointToLineDistance (const Eigen::Vector4f &pt, const Eigen::Vector4f &line_pt, const Eigen::Vector4f &line_dir, const double sqr_length)
 Get the square distance from a point to a line (represented by a point and a direction) More...
 
template<typename PointT >
double getMaxSegment (const pcl::PointCloud< PointT > &cloud, PointT &pmin, PointT &pmax)
 Obtain the maximum segment in a given set of points, and return the minimum and maximum points. More...
 
template<typename PointT >
double getMaxSegment (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, PointT &pmin, PointT &pmax)
 Obtain the maximum segment in a given set of points, and return the minimum and maximum points. More...
 
template<typename PointType1 , typename PointType2 >
float squaredEuclideanDistance (const PointType1 &p1, const PointType2 &p2)
 Calculate the squared euclidean distance between the two given points. More...
 
template<>
float squaredEuclideanDistance (const PointXY &p1, const PointXY &p2)
 Calculate the squared euclidean distance between the two given points. More...
 
template<typename PointType1 , typename PointType2 >
float euclideanDistance (const PointType1 &p1, const PointType2 &p2)
 Calculate the euclidean distance between the two given points. More...
 
template<typename Scalar , typename Roots >
void computeRoots2 (const Scalar &b, const Scalar &c, Roots &roots)
 Compute the roots of a quadratic polynom x^2 + b*x + c = 0. More...
 
template<typename Matrix , typename Roots >
void computeRoots (const Matrix &m, Roots &roots)
 computes the roots of the characteristic polynomial of the input matrix m, which are the eigenvalues More...
 
template<typename Matrix , typename Vector >
void eigen22 (const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
 determine the smallest eigenvalue and its corresponding eigenvector More...
 
template<typename Matrix , typename Vector >
void eigen22 (const Matrix &mat, Matrix &eigenvectors, Vector &eigenvalues)
 determine the smallest eigenvalue and its corresponding eigenvector More...
 
template<typename Matrix , typename Vector >
void computeCorrespondingEigenVector (const Matrix &mat, const typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
 determines the corresponding eigenvector to the given eigenvalue of the symmetric positive semi definite input matrix More...
 
template<typename Matrix , typename Vector >
void eigen33 (const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
 determines the eigenvector and eigenvalue of the smallest eigenvalue of the symmetric positive semi definite input matrix More...
 
template<typename Matrix , typename Vector >
void eigen33 (const Matrix &mat, Vector &evals)
 determines the eigenvalues of the symmetric positive semi definite input matrix More...
 
template<typename Matrix , typename Vector >
void eigen33 (const Matrix &mat, Matrix &evecs, Vector &evals)
 determines the eigenvalues and corresponding eigenvectors of the symmetric positive semi definite input matrix More...
 
template<typename Matrix >
Matrix::Scalar invert2x2 (const Matrix &matrix, Matrix &inverse)
 Calculate the inverse of a 2x2 matrix. More...
 
template<typename Matrix >
Matrix::Scalar invert3x3SymMatrix (const Matrix &matrix, Matrix &inverse)
 Calculate the inverse of a 3x3 symmetric matrix. More...
 
template<typename Matrix >
Matrix::Scalar invert3x3Matrix (const Matrix &matrix, Matrix &inverse)
 Calculate the inverse of a general 3x3 matrix. More...
 
template<typename Matrix >
Matrix::Scalar determinant3x3Matrix (const Matrix &matrix)
 Calculate the determinant of a 3x3 matrix. More...
 
void getTransFromUnitVectorsZY (const Eigen::Vector3f &z_axis, const Eigen::Vector3f &y_direction, Eigen::Affine3f &transformation)
 Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
 
Eigen::Affine3f getTransFromUnitVectorsZY (const Eigen::Vector3f &z_axis, const Eigen::Vector3f &y_direction)
 Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
 
void getTransFromUnitVectorsXY (const Eigen::Vector3f &x_axis, const Eigen::Vector3f &y_direction, Eigen::Affine3f &transformation)
 Get the unique 3D rotation that will rotate x_axis into (1,0,0) and y_direction into a vector with z=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
 
Eigen::Affine3f getTransFromUnitVectorsXY (const Eigen::Vector3f &x_axis, const Eigen::Vector3f &y_direction)
 Get the unique 3D rotation that will rotate x_axis into (1,0,0) and y_direction into a vector with z=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
 
void getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis, Eigen::Affine3f &transformation)
 Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
 
Eigen::Affine3f getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis)
 Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
 
void getTransformationFromTwoUnitVectorsAndOrigin (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis, const Eigen::Vector3f &origin, Eigen::Affine3f &transformation)
 Get the transformation that will translate orign to (0,0,0) and rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis) More...
 
template<typename Scalar >
void getEulerAngles (const Eigen::Transform< Scalar, 3, Eigen::Affine > &t, Scalar &roll, Scalar &pitch, Scalar &yaw)
 Extract the Euler angles (XYZ-convention) from the given transformation. More...
 
void getEulerAngles (const Eigen::Affine3f &t, float &roll, float &pitch, float &yaw)
 
void getEulerAngles (const Eigen::Affine3d &t, double &roll, double &pitch, double &yaw)
 
template<typename Scalar >
void getTranslationAndEulerAngles (const Eigen::Transform< Scalar, 3, Eigen::Affine > &t, Scalar &x, Scalar &y, Scalar &z, Scalar &roll, Scalar &pitch, Scalar &yaw)
 Extract x,y,z and the Euler angles (XYZ-convention) from the given transformation. More...
 
void getTranslationAndEulerAngles (const Eigen::Affine3f &t, float &x, float &y, float &z, float &roll, float &pitch, float &yaw)
 
void getTranslationAndEulerAngles (const Eigen::Affine3d &t, double &x, double &y, double &z, double &roll, double &pitch, double &yaw)
 
template<typename Scalar >
void getTransformation (Scalar x, Scalar y, Scalar z, Scalar roll, Scalar pitch, Scalar yaw, Eigen::Transform< Scalar, 3, Eigen::Affine > &t)
 Create a transformation from the given translation and Euler angles (XYZ-convention) More...
 
void getTransformation (float x, float y, float z, float roll, float pitch, float yaw, Eigen::Affine3f &t)
 
void getTransformation (double x, double y, double z, double roll, double pitch, double yaw, Eigen::Affine3d &t)
 
Eigen::Affine3f getTransformation (float x, float y, float z, float roll, float pitch, float yaw)
 Create a transformation from the given translation and Euler angles (XYZ-convention) More...
 
template<typename Derived >
void saveBinary (const Eigen::MatrixBase< Derived > &matrix, std::ostream &file)
 Write a matrix to an output stream. More...
 
template<typename Derived >
void loadBinary (Eigen::MatrixBase< Derived > const &matrix, std::istream &file)
 Read a matrix from an input stream. More...
 
template<typename Derived , typename OtherDerived >
Eigen::internal::umeyama_transform_matrix_type
< Derived, OtherDerived >
::type 
umeyama (const Eigen::MatrixBase< Derived > &src, const Eigen::MatrixBase< OtherDerived > &dst, bool with_scaling=false)
 Returns the transformation between two point sets. More...
 
template<typename Scalar >
void transformPoint (const Eigen::Matrix< Scalar, 3, 1 > &point_in, Eigen::Matrix< Scalar, 3, 1 > &point_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
 Transform a point using an affine matrix. More...
 
void transformPoint (const Eigen::Vector3f &point_in, Eigen::Vector3f &point_out, const Eigen::Affine3f &transformation)
 
void transformPoint (const Eigen::Vector3d &point_in, Eigen::Vector3d &point_out, const Eigen::Affine3d &transformation)
 
template<typename Scalar >
void transformVector (const Eigen::Matrix< Scalar, 3, 1 > &vector_in, Eigen::Matrix< Scalar, 3, 1 > &vector_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
 Transform a vector using an affine matrix. More...
 
void transformVector (const Eigen::Vector3f &vector_in, Eigen::Vector3f &vector_out, const Eigen::Affine3f &transformation)
 
void transformVector (const Eigen::Vector3d &vector_in, Eigen::Vector3d &vector_out, const Eigen::Affine3d &transformation)
 
template<typename Scalar >
bool transformLine (const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_in, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
 Transform a line using an affine matrix. More...
 
bool transformLine (const Eigen::VectorXf &line_in, Eigen::VectorXf &line_out, const Eigen::Affine3f &transformation)
 
bool transformLine (const Eigen::VectorXd &line_in, Eigen::VectorXd &line_out, const Eigen::Affine3d &transformation)
 
template<typename Scalar >
void transformPlane (const Eigen::Matrix< Scalar, 4, 1 > &plane_in, Eigen::Matrix< Scalar, 4, 1 > &plane_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
 Transform plane vectors using an affine matrix. More...
 
void transformPlane (const Eigen::Matrix< double, 4, 1 > &plane_in, Eigen::Matrix< double, 4, 1 > &plane_out, const Eigen::Transform< double, 3, Eigen::Affine > &transformation)
 
void transformPlane (const Eigen::Matrix< float, 4, 1 > &plane_in, Eigen::Matrix< float, 4, 1 > &plane_out, const Eigen::Transform< float, 3, Eigen::Affine > &transformation)
 
template<typename Scalar >
void transformPlane (const pcl::ModelCoefficients::Ptr plane_in, pcl::ModelCoefficients::Ptr plane_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
 Transform plane vectors using an affine matrix. More...
 
void transformPlane (const pcl::ModelCoefficients::Ptr plane_in, pcl::ModelCoefficients::Ptr plane_out, const Eigen::Transform< double, 3, Eigen::Affine > &transformation)
 
void transformPlane (const pcl::ModelCoefficients::Ptr plane_in, pcl::ModelCoefficients::Ptr plane_out, const Eigen::Transform< float, 3, Eigen::Affine > &transformation)
 
template<typename Scalar >
bool checkCoordinateSystem (const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_x, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line_y, const Scalar norm_limit=1e-3, const Scalar dot_limit=1e-3)
 Check coordinate system integrity. More...
 
bool checkCoordinateSystem (const Eigen::Matrix< double, Eigen::Dynamic, 1 > &line_x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > &line_y, const double norm_limit=1e-3, const double dot_limit=1e-3)
 
bool checkCoordinateSystem (const Eigen::Matrix< float, Eigen::Dynamic, 1 > &line_x, const Eigen::Matrix< float, Eigen::Dynamic, 1 > &line_y, const float norm_limit=1e-3, const float dot_limit=1e-3)
 
template<typename Scalar >
bool checkCoordinateSystem (const Eigen::Matrix< Scalar, 3, 1 > &origin, const Eigen::Matrix< Scalar, 3, 1 > &x_direction, const Eigen::Matrix< Scalar, 3, 1 > &y_direction, const Scalar norm_limit=1e-3, const Scalar dot_limit=1e-3)
 Check coordinate system integrity. More...
 
bool checkCoordinateSystem (const Eigen::Matrix< double, 3, 1 > &origin, const Eigen::Matrix< double, 3, 1 > &x_direction, const Eigen::Matrix< double, 3, 1 > &y_direction, const double norm_limit=1e-3, const double dot_limit=1e-3)
 
bool checkCoordinateSystem (const Eigen::Matrix< float, 3, 1 > &origin, const Eigen::Matrix< float, 3, 1 > &x_direction, const Eigen::Matrix< float, 3, 1 > &y_direction, const float norm_limit=1e-3, const float dot_limit=1e-3)
 
template<typename Scalar >
bool transformBetween2CoordinateSystems (const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > from_line_x, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > from_line_y, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > to_line_x, const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > to_line_y, Eigen::Transform< Scalar, 3, Eigen::Affine > &transformation)
 Compute the transformation between two coordinate systems. More...
 
bool transformBetween2CoordinateSystems (const Eigen::Matrix< double, Eigen::Dynamic, 1 > from_line_x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > from_line_y, const Eigen::Matrix< double, Eigen::Dynamic, 1 > to_line_x, const Eigen::Matrix< double, Eigen::Dynamic, 1 > to_line_y, Eigen::Transform< double, 3, Eigen::Affine > &transformation)
 
bool transformBetween2CoordinateSystems (const Eigen::Matrix< float, Eigen::Dynamic, 1 > from_line_x, const Eigen::Matrix< float, Eigen::Dynamic, 1 > from_line_y, const Eigen::Matrix< float, Eigen::Dynamic, 1 > to_line_x, const Eigen::Matrix< float, Eigen::Dynamic, 1 > to_line_y, Eigen::Transform< float, 3, Eigen::Affine > &transformation)
 
void getAllPcdFilesInDirectory (const std::string &directory, std::vector< std::string > &file_names)
 Find all *.pcd files in the directory and return them sorted. More...
 
std::string getFilenameWithoutPath (const std::string &input)
 Remove the path from the given string and return only the filename (the remaining string after the last '/') More...
 
std::string getFilenameWithoutExtension (const std::string &input)
 Remove the extension from the given string and return only the filename (everything before the last '. More...
 
std::string getFileExtension (const std::string &input)
 Get the file extension from the given string (the remaining string after the last '. More...
 
template<typename FloatVectorT >
float selectNorm (FloatVectorT A, FloatVectorT B, int dim, NormType norm_type)
 Method that calculates any norm type available, based on the norm_type variable. More...
 
template<typename FloatVectorT >
float L1_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the L1 norm of the vector between two points. More...
 
template<typename FloatVectorT >
float L2_Norm_SQR (FloatVectorT A, FloatVectorT B, int dim)
 Compute the squared L2 norm of the vector between two points. More...
 
template<typename FloatVectorT >
float L2_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the L2 norm of the vector between two points. More...
 
template<typename FloatVectorT >
float Linf_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the L-infinity norm of the vector between two points. More...
 
template<typename FloatVectorT >
float JM_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the JM norm of the vector between two points. More...
 
template<typename FloatVectorT >
float B_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the B norm of the vector between two points. More...
 
template<typename FloatVectorT >
float Sublinear_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the sublinear norm of the vector between two points. More...
 
template<typename FloatVectorT >
float CS_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the CS norm of the vector between two points. More...
 
template<typename FloatVectorT >
float Div_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the div norm of the vector between two points. More...
 
template<typename FloatVectorT >
float PF_Norm (FloatVectorT A, FloatVectorT B, int dim, float P1, float P2)
 Compute the PF norm of the vector between two points. More...
 
template<typename FloatVectorT >
float K_Norm (FloatVectorT A, FloatVectorT B, int dim, float P1, float P2)
 Compute the K norm of the vector between two points. More...
 
template<typename FloatVectorT >
float KL_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the KL between two discrete probability density functions. More...
 
template<typename FloatVectorT >
float HIK_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the HIK norm of the vector between two points. More...
 
PCL_EXPORTS bool lineWithLineIntersection (const Eigen::VectorXf &line_a, const Eigen::VectorXf &line_b, Eigen::Vector4f &point, double sqr_eps=1e-4)
 Get the intersection of a two 3D lines in space as a 3D point. More...
 
PCL_EXPORTS bool lineWithLineIntersection (const pcl::ModelCoefficients &line_a, const pcl::ModelCoefficients &line_b, Eigen::Vector4f &point, double sqr_eps=1e-4)
 Get the intersection of a two 3D lines in space as a 3D point. More...
 
template<typename Scalar >
PCL_EXPORTS bool planeWithPlaneIntersection (const Eigen::Matrix< Scalar, 4, 1 > &plane_a, const Eigen::Matrix< Scalar, 4, 1 > &plane_b, Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &line, double angular_tolerance=0.1)
 Determine the line of intersection of two non-parallel planes using lagrange multipliers. More...
 
PCL_EXPORTS bool planeWithPlaneIntersection (const Eigen::Vector4f &plane_a, const Eigen::Vector4f &plane_b, Eigen::VectorXf &line, double angular_tolerance=0.1)
 
PCL_EXPORTS bool planeWithPlaneIntersection (const Eigen::Vector4d &plane_a, const Eigen::Vector4d &plane_b, Eigen::VectorXd &line, double angular_tolerance=0.1)
 
template<typename Scalar >
PCL_EXPORTS bool threePlanesIntersection (const Eigen::Matrix< Scalar, 4, 1 > &plane_a, const Eigen::Matrix< Scalar, 4, 1 > &plane_b, const Eigen::Matrix< Scalar, 4, 1 > &plane_c, Eigen::Matrix< Scalar, 3, 1 > &intersection_point, double determinant_tolerance=1e-6)
 Determine the point of intersection of three non-parallel planes by solving the equations. More...
 
PCL_EXPORTS bool threePlanesIntersection (const Eigen::Vector4f &plane_a, const Eigen::Vector4f &plane_b, const Eigen::Vector4f &plane_c, Eigen::Vector3f &intersection_point, double determinant_tolerance=1e-6)
 
PCL_EXPORTS bool threePlanesIntersection (const Eigen::Vector4d &plane_a, const Eigen::Vector4d &plane_b, const Eigen::Vector4d &plane_c, Eigen::Vector3d &intersection_point, double determinant_tolerance=1e-6)
 
int getFieldIndex (const pcl::PCLPointCloud2 &cloud, const std::string &field_name)
 Get the index of a specified field (i.e., dimension/channel) More...
 
template<typename PointT >
int getFieldIndex (const pcl::PointCloud< PointT > &cloud, const std::string &field_name, std::vector< pcl::PCLPointField > &fields)
 Get the index of a specified field (i.e., dimension/channel) More...
 
template<typename PointT >
int getFieldIndex (const std::string &field_name, std::vector< pcl::PCLPointField > &fields)
 Get the index of a specified field (i.e., dimension/channel) More...
 
template<typename PointT >
void getFields (const pcl::PointCloud< PointT > &cloud, std::vector< pcl::PCLPointField > &fields)
 Get the list of available fields (i.e., dimension/channel) More...
 
template<typename PointT >
void getFields (std::vector< pcl::PCLPointField > &fields)
 Get the list of available fields (i.e., dimension/channel) More...
 
template<typename PointT >
std::string getFieldsList (const pcl::PointCloud< PointT > &cloud)
 Get the list of all fields available in a given cloud. More...
 
std::string getFieldsList (const pcl::PCLPointCloud2 &cloud)
 Get the available point cloud fields as a space separated string. More...
 
int getFieldSize (const int datatype)
 Obtains the size of a specific field data type in bytes. More...
 
PCL_EXPORTS void getFieldsSizes (const std::vector< pcl::PCLPointField > &fields, std::vector< int > &field_sizes)
 Obtain a vector with the sizes of all valid fields (e.g., not "_") More...
 
int getFieldType (const int size, char type)
 Obtains the type of the PCLPointField from a specific size and type. More...
 
char getFieldType (const int type)
 Obtains the type of the PCLPointField from a specific PCLPointField as a char. More...
 
PCL_EXPORTS int interpolatePointIndex (int p, int length, InterpolationType type)
 
PCL_EXPORTS bool concatenatePointCloud (const pcl::PCLPointCloud2 &cloud1, const pcl::PCLPointCloud2 &cloud2, pcl::PCLPointCloud2 &cloud_out)
 Concatenate two pcl::PCLPointCloud2. More...
 
PCL_EXPORTS void copyPointCloud (const pcl::PCLPointCloud2 &cloud_in, const std::vector< int > &indices, pcl::PCLPointCloud2 &cloud_out)
 Extract the indices of a given point cloud as a new point cloud. More...
 
PCL_EXPORTS void copyPointCloud (const pcl::PCLPointCloud2 &cloud_in, const std::vector< int, Eigen::aligned_allocator< int > > &indices, pcl::PCLPointCloud2 &cloud_out)
 Extract the indices of a given point cloud as a new point cloud. More...
 
PCL_EXPORTS void copyPointCloud (const pcl::PCLPointCloud2 &cloud_in, pcl::PCLPointCloud2 &cloud_out)
 Copy fields and point cloud data from cloud_in to cloud_out. More...
 
template<typename Point1T , typename Point2T >
bool isSamePointType ()
 Check if two given point types are the same or not. More...
 
template<typename PointT >
void copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out)
 Extract the indices of a given point cloud as a new point cloud. More...
 
template<typename PointT >
void copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int, Eigen::aligned_allocator< int > > &indices, pcl::PointCloud< PointT > &cloud_out)
 Extract the indices of a given point cloud as a new point cloud. More...
 
template<typename PointT >
void copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const PointIndices &indices, pcl::PointCloud< PointT > &cloud_out)
 Extract the indices of a given point cloud as a new point cloud. More...
 
template<typename PointT >
void copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< pcl::PointIndices > &indices, pcl::PointCloud< PointT > &cloud_out)
 Extract the indices of a given point cloud as a new point cloud. More...
 
template<typename PointInT , typename PointOutT >
void copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, pcl::PointCloud< PointOutT > &cloud_out)
 Copy all the fields from a given point cloud into a new point cloud. More...
 
template<typename PointInT , typename PointOutT >
void copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointOutT > &cloud_out)
 Extract the indices of a given point cloud as a new point cloud. More...
 
template<typename PointInT , typename PointOutT >
void copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const std::vector< int, Eigen::aligned_allocator< int > > &indices, pcl::PointCloud< PointOutT > &cloud_out)
 Extract the indices of a given point cloud as a new point cloud. More...
 
template<typename PointInT , typename PointOutT >
void copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const PointIndices &indices, pcl::PointCloud< PointOutT > &cloud_out)
 Extract the indices of a given point cloud as a new point cloud. More...
 
template<typename PointInT , typename PointOutT >
void copyPointCloud (const pcl::PointCloud< PointInT > &cloud_in, const std::vector< pcl::PointIndices > &indices, pcl::PointCloud< PointOutT > &cloud_out)
 Extract the indices of a given point cloud as a new point cloud. More...
 
template<typename PointT >
void copyPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, int top, int bottom, int left, int right, pcl::InterpolationType border_type, const PointT &value)
 Copy a point cloud inside a larger one interpolating borders. More...
 
template<typename PointIn1T , typename PointIn2T , typename PointOutT >
void concatenateFields (const pcl::PointCloud< PointIn1T > &cloud1_in, const pcl::PointCloud< PointIn2T > &cloud2_in, pcl::PointCloud< PointOutT > &cloud_out)
 Concatenate two datasets representing different fields. More...
 
PCL_EXPORTS bool concatenateFields (const pcl::PCLPointCloud2 &cloud1_in, const pcl::PCLPointCloud2 &cloud2_in, pcl::PCLPointCloud2 &cloud_out)
 Concatenate two datasets representing different fields. More...
 
PCL_EXPORTS bool getPointCloudAsEigen (const pcl::PCLPointCloud2 &in, Eigen::MatrixXf &out)
 Copy the XYZ dimensions of a pcl::PCLPointCloud2 into Eigen format. More...
 
PCL_EXPORTS bool getEigenAsPointCloud (Eigen::MatrixXf &in, pcl::PCLPointCloud2 &out)
 Copy the XYZ dimensions from an Eigen MatrixXf into a pcl::PCLPointCloud2 message. More...
 
template<typename PointT >
bool isFinite (const PointT &pt)
 Tests if the 3D components of a point are all finite param[in] pt point to be tested return true if finite, false otherwise. More...
 
template<>
bool isFinite< pcl::RGB > (const pcl::RGB &)
 
template<>
bool isFinite< pcl::Label > (const pcl::Label &)
 
template<>
bool isFinite< pcl::Axis > (const pcl::Axis &)
 
template<>
bool isFinite< pcl::Intensity > (const pcl::Intensity &)
 
template<>
bool isFinite< pcl::MomentInvariants > (const pcl::MomentInvariants &)
 
template<>
bool isFinite< pcl::PrincipalRadiiRSD > (const pcl::PrincipalRadiiRSD &)
 
template<>
bool isFinite< pcl::Boundary > (const pcl::Boundary &)
 
template<>
bool isFinite< pcl::PrincipalCurvatures > (const pcl::PrincipalCurvatures &)
 
template<>
bool isFinite< pcl::SHOT352 > (const pcl::SHOT352 &)
 
template<>
bool isFinite< pcl::SHOT1344 > (const pcl::SHOT1344 &)
 
template<>
bool isFinite< pcl::ReferenceFrame > (const pcl::ReferenceFrame &)
 
template<>
bool isFinite< pcl::ShapeContext1980 > (const pcl::ShapeContext1980 &)
 
template<>
bool isFinite< pcl::UniqueShapeContext1960 > (const pcl::UniqueShapeContext1960 &)
 
template<>
bool isFinite< pcl::PFHSignature125 > (const pcl::PFHSignature125 &)
 
template<>
bool isFinite< pcl::PFHRGBSignature250 > (const pcl::PFHRGBSignature250 &)
 
template<>
bool isFinite< pcl::PPFSignature > (const pcl::PPFSignature &)
 
template<>
bool isFinite< pcl::PPFRGBSignature > (const pcl::PPFRGBSignature &)
 
template<>
bool isFinite< pcl::NormalBasedSignature12 > (const pcl::NormalBasedSignature12 &)
 
template<>
bool isFinite< pcl::FPFHSignature33 > (const pcl::FPFHSignature33 &)
 
template<>
bool isFinite< pcl::VFHSignature308 > (const pcl::VFHSignature308 &)
 
template<>
bool isFinite< pcl::ESFSignature640 > (const pcl::ESFSignature640 &)
 
template<>
bool isFinite< pcl::IntensityGradient > (const pcl::IntensityGradient &)
 
template<>
bool isFinite< pcl::BRISKSignature512 > (const pcl::BRISKSignature512 &)
 
template<>
bool isFinite< pcl::PointXY > (const pcl::PointXY &p)
 
template<>
bool isFinite< pcl::BorderDescription > (const pcl::BorderDescription &p)
 
template<>
bool isFinite< pcl::Normal > (const pcl::Normal &n)
 
template<typename PointT >
double estimateProjectionMatrix (typename pcl::PointCloud< PointT >::ConstPtr cloud, Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &projection_matrix, const std::vector< int > &indices=std::vector< int >())
 Estimates the projection matrix P = K * (R|-R*t) from organized point clouds, with K = [[fx, s, cx], [0, fy, cy], [0, 0, 1]] R = rotation matrix and t = translation vector. More...
 
PCL_EXPORTS void getCameraMatrixFromProjectionMatrix (const Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &projection_matrix, Eigen::Matrix3f &camera_matrix)
 Determines the camera matrix from the given projection matrix. More...
 
double getTime ()
 
template<typename PointT , typename Scalar >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
 Apply an affine transform defined by an Eigen Transform. More...
 
template<typename PointT >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
 Apply an affine transform defined by an Eigen Transform. More...
 
template<typename PointT >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
 Apply an affine transform defined by an Eigen Transform. More...
 
template<typename PointT >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
 Transform a point cloud and rotate its normals using an Eigen transform. More...
 
template<typename PointT >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
 Transform a point cloud and rotate its normals using an Eigen transform. More...
 
template<typename PointT >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform, bool copy_all_fields=true)
 Transform a point cloud and rotate its normals using an Eigen transform. More...
 
template<typename PointT >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
 Apply a rigid transform defined by a 4x4 matrix. More...
 
template<typename PointT >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
 Apply a rigid transform defined by a 4x4 matrix. More...
 
template<typename PointT >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
 Apply a rigid transform defined by a 4x4 matrix. More...
 
template<typename PointT >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
 Transform a point cloud and rotate its normals using an Eigen transform. More...
 
template<typename PointT >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
 Transform a point cloud and rotate its normals using an Eigen transform. More...
 
template<typename PointT >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 4, 4 > &transform, bool copy_all_fields=true)
 Transform a point cloud and rotate its normals using an Eigen transform. More...
 
template<typename PointT >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &indices, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 3, 1 > &offset, const Eigen::Quaternion< Scalar > &rotation, bool copy_all_fields=true)
 Apply a rigid transform defined by a 3D offset and a quaternion. More...
 
template<typename PointT >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Vector3f &offset, const Eigen::Quaternionf &rotation, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix< Scalar, 3, 1 > &offset, const Eigen::Quaternion< Scalar > &rotation, bool copy_all_fields=true)
 Transform a point cloud and rotate its normals using an Eigen transform. More...
 
template<typename PointT >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Vector3f &offset, const Eigen::Quaternionf &rotation, bool copy_all_fields=true)
 
template<typename PointT , typename Scalar >
PointT transformPoint (const PointT &point, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform)
 Transform a point with members x,y,z. More...
 
template<typename PointT >
PointT transformPoint (const PointT &point, const Eigen::Affine3f &transform)
 
template<typename PointT , typename Scalar >
PointT transformPointWithNormal (const PointT &point, const Eigen::Transform< Scalar, 3, Eigen::Affine > &transform)
 Transform a point with members x,y,z,normal_x,normal_y,normal_z. More...
 
template<typename PointT >
PointT transformPointWithNormal (const PointT &point, const Eigen::Affine3f &transform)
 
template<typename PointT , typename Scalar >
double getPrincipalTransformation (const pcl::PointCloud< PointT > &cloud, Eigen::Transform< Scalar, 3, Eigen::Affine > &transform)
 Calculates the principal (PCA-based) alignment of the point cloud. More...
 
template<typename PointT >
double getPrincipalTransformation (const pcl::PointCloud< PointT > &cloud, Eigen::Affine3f &transform)
 
template<typename PointT >
void createMapping (const std::vector< pcl::PCLPointField > &msg_fields, MsgFieldMap &field_map)
 
template<typename PointT >
void fromPCLPointCloud2 (const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map)
 Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map. More...
 
template<typename PointT >
void fromPCLPointCloud2 (const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud)
 Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object. More...
 
template<typename PointT >
void toPCLPointCloud2 (const pcl::PointCloud< PointT > &cloud, pcl::PCLPointCloud2 &msg)
 Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob. More...
 
template<typename CloudT >
void toPCLPointCloud2 (const CloudT &cloud, pcl::PCLImage &msg)
 Copy the RGB fields of a PointCloud into pcl::PCLImage format. More...
 
void toPCLPointCloud2 (const pcl::PCLPointCloud2 &cloud, pcl::PCLImage &msg)
 Copy the RGB fields of a PCLPointCloud2 msg into pcl::PCLImage format. More...
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const Correspondence &c)
 overloaded << operator More...
 
void getRejectedQueryIndices (const pcl::Correspondences &correspondences_before, const pcl::Correspondences &correspondences_after, std::vector< int > &indices, bool presorting_required=true)
 Get the query points of correspondences that are present in one correspondence vector but not in the other, e.g., to compare correspondences before and after rejection. More...
 
bool isBetterCorrespondence (const Correspondence &pc1, const Correspondence &pc2)
 Comparator to enable us to sort a vector of PointCorrespondences according to their scores using std::sort (begin(), end(), isBetterCorrespondence);. More...
 
template<typename Sequence , typename F >
void for_each_type (F f)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXYZ &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const RGB &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const Intensity &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const Intensity8u &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const Intensity32u &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXYZI &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXYZL &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const Label &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXYZRGBA &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXYZRGB &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXYZRGBL &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXYZHSV &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXY &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointUV &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const InterestPoint &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const Normal &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const Axis &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointNormal &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXYZRGBNormal &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXYZINormal &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointXYZLNormal &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointWithRange &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointWithViewpoint &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const MomentInvariants &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PrincipalRadiiRSD &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const Boundary &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PrincipalCurvatures &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PFHSignature125 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PFHRGBSignature250 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PPFSignature &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const CPPFSignature &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PPFRGBSignature &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const NormalBasedSignature12 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const ShapeContext1980 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const UniqueShapeContext1960 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const SHOT352 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const SHOT1344 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const ReferenceFrame &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const FPFHSignature33 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const VFHSignature308 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const GRSDSignature21 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const BRISKSignature512 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const ESFSignature640 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const GFPFHSignature16 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const Narf36 &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const BorderDescription &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const IntensityGradient &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointWithScale &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointSurfel &p)
 
PCL_EXPORTS std::ostream & operator<< (std::ostream &os, const PointDEM &p)
 
template<int N>
std::ostream & operator<< (std::ostream &os, const Histogram< N > &p)
 
std::ostream & operator<< (std::ostream &s, const ::pcl::ModelCoefficients &v)
 
std::ostream & operator<< (std::ostream &out, const PCLHeader &h)
 
bool operator== (const PCLHeader &lhs, const PCLHeader &rhs)
 
std::ostream & operator<< (std::ostream &s, const ::pcl::PCLImage &v)
 
std::ostream & operator<< (std::ostream &s, const ::pcl::PCLPointCloud2 &v)
 
std::ostream & operator<< (std::ostream &s, const ::pcl::PCLPointField &v)
 
template<typename PointT >
std::ostream & operator<< (std::ostream &s, const pcl::PointCloud< PointT > &p)
 
template<typename PointT , typename ValT >
void setFieldValue (PointT &pt, size_t field_offset, const ValT &value)
 Set the value at a specified field in a point. More...
 
template<typename PointT , typename ValT >
void getFieldValue (const PointT &pt, size_t field_offset, ValT &value)
 Get the value at a specified field in a point. More...
 
void PointXYZRGBtoXYZI (const PointXYZRGB &in, PointXYZI &out)
 Convert a XYZRGB point type to a XYZI. More...
 
void PointRGBtoI (const RGB &in, Intensity &out)
 Convert a RGB point type to a I. More...
 
void PointRGBtoI (const RGB &in, Intensity8u &out)
 Convert a RGB point type to a I. More...
 
void PointRGBtoI (const RGB &in, Intensity32u &out)
 Convert a RGB point type to a I. More...
 
void PointXYZRGBtoXYZHSV (const PointXYZRGB &in, PointXYZHSV &out)
 Convert a XYZRGB point type to a XYZHSV. More...
 
void PointXYZRGBAtoXYZHSV (const PointXYZRGBA &in, PointXYZHSV &out)
 Convert a XYZRGB point type to a XYZHSV. More...
 
void PointXYZHSVtoXYZRGB (const PointXYZHSV &in, PointXYZRGB &out)
 
void PointCloudRGBtoI (const PointCloud< RGB > &in, PointCloud< Intensity > &out)
 Convert a RGB point cloud to a Intensity. More...
 
void PointCloudRGBtoI (const PointCloud< RGB > &in, PointCloud< Intensity8u > &out)
 Convert a RGB point cloud to a Intensity. More...
 
void PointCloudRGBtoI (const PointCloud< RGB > &in, PointCloud< Intensity32u > &out)
 Convert a RGB point cloud to a Intensity. More...
 
void PointCloudXYZRGBtoXYZHSV (const PointCloud< PointXYZRGB > &in, PointCloud< PointXYZHSV > &out)
 Convert a XYZRGB point cloud to a XYZHSV. More...
 
void PointCloudXYZRGBAtoXYZHSV (const PointCloud< PointXYZRGBA > &in, PointCloud< PointXYZHSV > &out)
 Convert a XYZRGB point cloud to a XYZHSV. More...
 
void PointCloudXYZRGBtoXYZI (const PointCloud< PointXYZRGB > &in, PointCloud< PointXYZI > &out)
 Convert a XYZRGB point cloud to a XYZI. More...
 
void PointCloudDepthAndRGBtoXYZRGBA (const PointCloud< Intensity > &depth, const PointCloud< RGB > &image, const float &focal, PointCloud< PointXYZRGBA > &out)
 Convert registered Depth image and RGB image to PointCloudXYZRGBA. More...
 
std::ostream & operator<< (std::ostream &s, const ::pcl::PointIndices &v)
 
std::ostream & operator<< (std::ostream &s, const ::pcl::PolygonMesh &v)
 
std::ostream & operator<< (std::ostream &os, const RangeImage &r)
 /ingroup range_image More...
 
template<typename PointT >
void fromROSMsg (const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map)
 Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map. More...
 
template<typename PointT >
void fromROSMsg (const pcl::PCLPointCloud2 &msg, pcl::PointCloud< PointT > &cloud)
 Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object. More...
 
template<typename PointT >
void toROSMsg (const pcl::PointCloud< PointT > &cloud, pcl::PCLPointCloud2 &msg)
 Convert a pcl::PointCloud<T> object to a PCLPointCloud2 binary data blob. More...
 
template<typename CloudT >
void toROSMsg (const CloudT &cloud, pcl::PCLImage &msg)
 Copy the RGB fields of a PointCloud into pcl::PCLImage format. More...
 
void toROSMsg (const pcl::PCLPointCloud2 &cloud, pcl::PCLImage &msg)
 Copy the RGB fields of a PCLPointCloud2 msg into pcl::PCLImage format. More...
 
std::ostream & operator<< (std::ostream &s, const ::pcl::Vertices &v)
 
PCL_EXPORTS bool computeCPPFPairFeature (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4i &c1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, const Eigen::Vector4i &c2, float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7, float &f8, float &f9, float &f10)
 
void solvePlaneParameters (const Eigen::Matrix3f &covariance_matrix, const Eigen::Vector4f &point, Eigen::Vector4f &plane_parameters, float &curvature)
 Solve the eigenvalues and eigenvectors of a given 3x3 covariance matrix, and estimate the least-squares plane normal and surface curvature. More...
 
void solvePlaneParameters (const Eigen::Matrix3f &covariance_matrix, float &nx, float &ny, float &nz, float &curvature)
 Solve the eigenvalues and eigenvectors of a given 3x3 covariance matrix, and estimate the least-squares plane normal and surface curvature. More...
 
std::ostream & operator<< (std::ostream &os, const RangeImageBorderExtractor::Parameters &p)
 
template<typename PointT >
bool computePointNormal (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &plane_parameters, float &curvature)
 Compute the Least-Squares plane fit for a given set of points, and return the estimated plane parameters together with the surface curvature. More...
 
template<typename PointT >
bool computePointNormal (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Vector4f &plane_parameters, float &curvature)
 Compute the Least-Squares plane fit for a given set of points, using their indices, and return the estimated plane parameters together with the surface curvature. More...
 
template<typename PointT , typename Scalar >
void flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Matrix< Scalar, 4, 1 > &normal)
 Flip (in place) the estimated normal of a point towards a given viewpoint. More...
 
template<typename PointT , typename Scalar >
void flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Matrix< Scalar, 3, 1 > &normal)
 Flip (in place) the estimated normal of a point towards a given viewpoint. More...
 
template<typename PointT >
void flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, float &nx, float &ny, float &nz)
 Flip (in place) the estimated normal of a point towards a given viewpoint. More...
 
PCL_EXPORTS bool computePairFeatures (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, float &f1, float &f2, float &f3, float &f4)
 Compute the 4-tuple representation containing the three angles and one distance between two points represented by Cartesian coordinates and normals. More...
 
PCL_EXPORTS bool computeRGBPairFeatures (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4i &colors1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, const Eigen::Vector4i &colors2, float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7)
 
PCL_EXPORTS bool computePPFPairFeature (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, float &f1, float &f2, float &f3, float &f4)
 
template<int N>
void getFeaturePointCloud (const std::vector< Eigen::MatrixXf, Eigen::aligned_allocator< Eigen::MatrixXf > > &histograms2D, PointCloud< Histogram< N > > &histogramsPC)
 Transform a list of 2D matrices into a point cloud containing the values in a vector (Histogram<N>). More...
 
template<typename PointInT , typename PointNT , typename PointOutT >
Eigen::MatrixXf computeRSD (boost::shared_ptr< const pcl::PointCloud< PointInT > > &surface, boost::shared_ptr< const pcl::PointCloud< PointNT > > &normals, const std::vector< int > &indices, double max_dist, int nr_subdiv, double plane_radius, PointOutT &radii, bool compute_histogram=false)
 Estimate the Radius-based Surface Descriptor (RSD) for a given point based on its spatial neighborhood of 3D points with normals. More...
 
template<typename PointNT , typename PointOutT >
Eigen::MatrixXf computeRSD (boost::shared_ptr< const pcl::PointCloud< PointNT > > &normals, const std::vector< int > &indices, const std::vector< float > &sqr_dists, double max_dist, int nr_subdiv, double plane_radius, PointOutT &radii, bool compute_histogram=false)
 Estimate the Radius-based Surface Descriptor (RSD) for a given point based on its spatial neighborhood of 3D points with normals. More...
 
template<typename PointT >
void removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, std::vector< int > &index)
 Removes points with x, y, or z equal to NaN. More...
 
template<typename PointT >
void removeNaNNormalsFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, std::vector< int > &index)
 Removes points that have their normals invalid (i.e., equal to NaN) More...
 
template<typename PointT >
void removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, std::vector< int > &index)
 Removes points with x, y, or z equal to NaN (dry run). More...
 
template<typename PointT >
PCL_EXPORTS void applyMorphologicalOperator (const typename pcl::PointCloud< PointT >::ConstPtr &cloud_in, float resolution, const int morphological_operator, pcl::PointCloud< PointT > &cloud_out)
 Apply morphological operator to the z dimension of the input point cloud. More...
 
template<typename NormalT >
std::vector< float > assignNormalWeights (const PointCloud< NormalT > &, int, const std::vector< int > &k_indices, const std::vector< float > &k_sqr_distances)
 Assign weights of nearby normals used for refinement. More...
 
template<typename NormalT >
bool refineNormal (const PointCloud< NormalT > &cloud, int index, const std::vector< int > &k_indices, const std::vector< float > &k_sqr_distances, NormalT &point)
 Refine an indexed point based on its neighbors, this function only writes to the normal_* fields. More...
 
PCL_EXPORTS void getMinMax3D (const pcl::PCLPointCloud2ConstPtr &cloud, int x_idx, int y_idx, int z_idx, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt)
 Obtain the maximum and minimum points in 3D from a given point cloud. More...
 
PCL_EXPORTS void getMinMax3D (const pcl::PCLPointCloud2ConstPtr &cloud, int x_idx, int y_idx, int z_idx, const std::string &distance_field_name, float min_distance, float max_distance, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative=false)
 Obtain the maximum and minimum points in 3D from a given point cloud. More...
 
Eigen::MatrixXi getHalfNeighborCellIndices ()
 Get the relative cell indices of the "upper half" 13 neighbors. More...
 
Eigen::MatrixXi getAllNeighborCellIndices ()
 Get the relative cell indices of all the 26 neighbors. More...
 
template<typename PointT >
void getMinMax3D (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, const std::string &distance_field_name, float min_distance, float max_distance, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative=false)
 Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud, without considering points outside of a distance threshold from the laser origin. More...
 
template<typename PointT >
void getMinMax3D (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, const std::vector< int > &indices, const std::string &distance_field_name, float min_distance, float max_distance, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt, bool limit_negative=false)
 Get the minimum and maximum values on each of the 3 (x-y-z) dimensions in a given pointcloud, without considering points outside of a distance threshold from the laser origin. More...
 
template<typename PointT >
void approximatePolygon (const PlanarPolygon< PointT > &polygon, PlanarPolygon< PointT > &approx_polygon, float threshold, bool refine=false, bool closed=true)
 see approximatePolygon2D More...
 
template<typename PointT >
void approximatePolygon2D (const typename PointCloud< PointT >::VectorType &polygon, typename PointCloud< PointT >::VectorType &approx_polygon, float threshold, bool refine=false, bool closed=true)
 returns an approximate polygon to given 2D contour. More...
 
template<typename Type >
void copyValueString (const pcl::PCLPointCloud2 &cloud, const unsigned int point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream)
 insers a value of type Type (uchar, char, uint, int, float, double, ...) into a stringstream. More...
 
template<>
void copyValueString< int8_t > (const pcl::PCLPointCloud2 &cloud, const unsigned int point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream)
 
template<>
void copyValueString< uint8_t > (const pcl::PCLPointCloud2 &cloud, const unsigned int point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream)
 
template<typename Type >
bool isValueFinite (const pcl::PCLPointCloud2 &cloud, const unsigned int point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count)
 Check whether a given value of type Type (uchar, char, uint, int, float, double, ...) is finite or not. More...
 
template<typename Type >
void copyStringValue (const std::string &st, pcl::PCLPointCloud2 &cloud, unsigned int point_index, unsigned int field_idx, unsigned int fields_count)
 Copy one single value of type T (uchar, char, uint, int, float, double, ...) from a string. More...
 
template<>
void copyStringValue< int8_t > (const std::string &st, pcl::PCLPointCloud2 &cloud, unsigned int point_index, unsigned int field_idx, unsigned int fields_count)
 
template<>
void copyStringValue< uint8_t > (const std::string &st, pcl::PCLPointCloud2 &cloud, unsigned int point_index, unsigned int field_idx, unsigned int fields_count)
 
PCL_EXPORTS unsigned int lzfCompress (const void *const in_data, unsigned int in_len, void *out_data, unsigned int out_len)
 Compress in_len bytes stored at the memory block starting at in_data and write the result to out_data, up to a maximum length of out_len bytes using Marc Lehmann's LZF algorithm. More...
 
PCL_EXPORTS unsigned int lzfDecompress (const void *const in_data, unsigned int in_len, void *out_data, unsigned int out_len)
 Decompress data compressed with the lzfCompress function and stored at location in_data and length in_len. More...
 
template<typename PointT >
void getApproximateIndices (const typename pcl::PointCloud< PointT >::ConstPtr &cloud_in, const typename pcl::PointCloud< PointT >::ConstPtr &cloud_ref, std::vector< int > &indices)
 Get a set of approximate indices for a given point cloud into a reference point cloud. More...
 
template<typename Point1T , typename Point2T >
void getApproximateIndices (const typename pcl::PointCloud< Point1T >::ConstPtr &cloud_in, const typename pcl::PointCloud< Point2T >::ConstPtr &cloud_ref, std::vector< int > &indices)
 Get a set of approximate indices for a given point cloud into a reference point cloud. More...
 
std::ostream & operator<< (std::ostream &os, const NarfKeypoint::Parameters &p)
 
std::ostream & operator<< (std::ostream &os, const GradientXY &p)
 
template<class Type >
void read (std::istream &stream, Type &value)
 Function for reading data from a stream. More...
 
template<class Type >
void read (std::istream &stream, Type *value, int nr_values)
 Function for reading data arrays from a stream. More...
 
template<class Type >
void write (std::ostream &stream, Type value)
 Function for writing data to a stream. More...
 
template<class Type >
void write (std::ostream &stream, Type *value, int nr_values)
 Function for writing data arrays to a stream. More...
 
template<typename PointT >
float getMeanPointDensity (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, float max_dist, int nr_threads=1)
 Compute the mean point density of a given point cloud. More...
 
template<typename PointT >
float getMeanPointDensity (const typename pcl::PointCloud< PointT >::ConstPtr &cloud, const std::vector< int > &indices, float max_dist, int nr_threads=1)
 Compute the mean point density of a given point cloud. More...
 
static const std::map
< pcl::SacModel, unsigned int > 
SAC_SAMPLE_SIZE (sample_size_pairs, sample_size_pairs+sizeof(sample_size_pairs)/sizeof(SampleSizeModel))
 
template<typename Point >
void projectPoint (const Point &p, const Eigen::Vector4f &model_coefficients, Point &q)
 Project a point on a planar model given by a set of normalized coefficients. More...
 
template<typename Point >
double pointToPlaneDistanceSigned (const Point &p, double a, double b, double c, double d)
 Get the distance from a point to a plane (signed) defined by ax+by+cz+d=0. More...
 
template<typename Point >
double pointToPlaneDistanceSigned (const Point &p, const Eigen::Vector4f &plane_coefficients)
 Get the distance from a point to a plane (signed) defined by ax+by+cz+d=0. More...
 
template<typename Point >
double pointToPlaneDistance (const Point &p, double a, double b, double c, double d)
 Get the distance from a point to a plane (unsigned) defined by ax+by+cz+d=0. More...
 
template<typename Point >
double pointToPlaneDistance (const Point &p, const Eigen::Vector4f &plane_coefficients)
 Get the distance from a point to a plane (unsigned) defined by ax+by+cz+d=0. More...
 
template<typename PointT >
void extractEuclideanClusters (const PointCloud< PointT > &cloud, const boost::shared_ptr< search::Search< PointT > > &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
 Decompose a region of space into clusters based on the Euclidean distance between points. More...
 
template<typename PointT >
void extractEuclideanClusters (const PointCloud< PointT > &cloud, const std::vector< int > &indices, const boost::shared_ptr< search::Search< PointT > > &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
 Decompose a region of space into clusters based on the Euclidean distance between points. More...
 
template<typename PointT , typename Normal >
void extractEuclideanClusters (const PointCloud< PointT > &cloud, const PointCloud< Normal > &normals, float tolerance, const boost::shared_ptr< KdTree< PointT > > &tree, std::vector< PointIndices > &clusters, double eps_angle, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
 Decompose a region of space into clusters based on the euclidean distance between points, and the normal angular deviation. More...
 
template<typename PointT , typename Normal >
void extractEuclideanClusters (const PointCloud< PointT > &cloud, const PointCloud< Normal > &normals, const std::vector< int > &indices, const boost::shared_ptr< KdTree< PointT > > &tree, float tolerance, std::vector< PointIndices > &clusters, double eps_angle, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
 Decompose a region of space into clusters based on the euclidean distance between points, and the normal angular deviation. More...
 
bool comparePointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b)
 Sort clusters method (for std::sort). More...
 
template<typename PointT >
void extractLabeledEuclideanClusters (const PointCloud< PointT > &cloud, const boost::shared_ptr< search::Search< PointT > > &tree, float tolerance, std::vector< std::vector< PointIndices > > &labeled_clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=std::numeric_limits< unsigned int >::max(), unsigned int max_label=std::numeric_limits< unsigned int >::max())
 Decompose a region of space into clusters based on the Euclidean distance between points. More...
 
bool compareLabeledPointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b)
 Sort clusters method (for std::sort). More...
 
template<typename PointT >
bool isPointIn2DPolygon (const PointT &point, const pcl::PointCloud< PointT > &polygon)
 General purpose method for checking if a 3D point is inside or outside a given 2D polygon. More...
 
template<typename PointT >
bool isXYPointIn2DXYPolygon (const PointT &point, const pcl::PointCloud< PointT > &polygon)
 Check if a 2d point (X and Y coordinates considered only!) is inside or outside a given polygon. More...
 
template<>
float squaredEuclideanDistance (const pcl::segmentation::grabcut::Color &c1, const pcl::segmentation::grabcut::Color &c2)
 
bool comparePair (std::pair< float, int > i, std::pair< float, int > j)
 This function is used as a comparator for sorting. More...
 
void seededHueSegmentation (const PointCloud< PointXYZRGB > &cloud, const boost::shared_ptr< search::Search< PointXYZRGB > > &tree, float tolerance, PointIndices &indices_in, PointIndices &indices_out, float delta_hue=0.0)
 Decompose a region of space into clusters based on the Euclidean distance between points. More...
 
void seededHueSegmentation (const PointCloud< PointXYZRGB > &cloud, const boost::shared_ptr< search::Search< PointXYZRGBL > > &tree, float tolerance, PointIndices &indices_in, PointIndices &indices_out, float delta_hue=0.0)
 Decompose a region of space into clusters based on the Euclidean distance between points. More...
 
template<typename PointT >
void getPointCloudDifference (const pcl::PointCloud< PointT > &src, const pcl::PointCloud< PointT > &tgt, double threshold, const boost::shared_ptr< pcl::search::Search< PointT > > &tree, pcl::PointCloud< PointT > &output)
 Obtain the difference between two aligned point clouds as another point cloud, given a distance threshold. More...
 
bool comparePoints2D (const std::pair< int, Eigen::Vector4f > &p1, const std::pair< int, Eigen::Vector4f > &p2)
 Sort 2D points in a vector structure. More...
 
bool isVisible (const Eigen::Vector2f &X, const Eigen::Vector2f &S1, const Eigen::Vector2f &S2, const Eigen::Vector2f &R=Eigen::Vector2f::Zero())
 Returns if a point X is visible from point R (or the origin) when taking into account the segment between the points S1 and S2. More...
 

Variables

struct pcl::PointXYZIEdge EIGEN_ALIGN16
 
static const int SAC_RANSAC = 0
 
static const int SAC_LMEDS = 1
 
static const int SAC_MSAC = 2
 
static const int SAC_RRANSAC = 3
 
static const int SAC_RMSAC = 4
 
static const int SAC_MLESAC = 5
 
static const int SAC_PROSAC = 6
 
const int I_SHIFT_EP [12][2]
 The 12 edges of a cell. More...
 
const int I_SHIFT_PT [4]
 
const int I_SHIFT_EDGE [3][2]
 
const unsigned int edgeTable [256]
 
const int triTable [256][16]
 

Typedef Documentation

typedef Eigen::Map<Eigen::Array3f> pcl::Array3fMap

Definition at line 157 of file point_types.hpp.

typedef const Eigen::Map<const Eigen::Array3f> pcl::Array3fMapConst

Definition at line 158 of file point_types.hpp.

typedef Eigen::Map<Eigen::Array4f, Eigen::Aligned> pcl::Array4fMap

Definition at line 159 of file point_types.hpp.

typedef const Eigen::Map<const Eigen::Array4f, Eigen::Aligned> pcl::Array4fMapConst

Definition at line 160 of file point_types.hpp.

Definition at line 137 of file bivariate_polynomial.h.

Definition at line 136 of file bivariate_polynomial.h.

typedef std::vector< pcl::Correspondence, Eigen::aligned_allocator<pcl::Correspondence> > pcl::Correspondences

Definition at line 92 of file correspondence.h.

typedef boost::shared_ptr<const Correspondences > pcl::CorrespondencesConstPtr

Definition at line 94 of file correspondence.h.

typedef boost::shared_ptr<Correspondences> pcl::CorrespondencesPtr

Definition at line 93 of file correspondence.h.

Definition at line 229 of file multi_channel_2d_data_set.h.

typedef boost::shared_ptr<PCLHeader const> pcl::HeaderConstPtr

Definition at line 36 of file PCLHeader.h.

typedef boost::shared_ptr<PCLHeader> pcl::HeaderPtr

Definition at line 35 of file PCLHeader.h.

Definition at line 48 of file conditional_euclidean_clustering.h.

typedef boost::shared_ptr<std::vector<pcl::PointIndices> > pcl::IndicesClustersPtr

Definition at line 49 of file conditional_euclidean_clustering.h.

typedef boost::shared_ptr<const std::vector<int> > pcl::IndicesConstPtr

Definition at line 61 of file pcl_base.h.

typedef boost::shared_ptr<std::vector<int> > pcl::IndicesPtr

Definition at line 60 of file pcl_base.h.

Definition at line 230 of file multi_channel_2d_data_set.h.

typedef boost::shared_ptr< ::pcl::ModelCoefficients const> pcl::ModelCoefficientsConstPtr

Definition at line 28 of file ModelCoefficients.h.

typedef boost::shared_ptr< ::pcl::ModelCoefficients> pcl::ModelCoefficientsPtr

Definition at line 27 of file ModelCoefficients.h.

typedef std::vector<detail::FieldMapping> pcl::MsgFieldMap

Definition at line 65 of file point_cloud.h.

typedef boost::shared_ptr< ::pcl::PCLImage const> pcl::PCLImageConstPtr

Definition at line 38 of file PCLImage.h.

typedef boost::shared_ptr< ::pcl::PCLImage> pcl::PCLImagePtr

Definition at line 37 of file PCLImage.h.

typedef boost::shared_ptr< ::pcl::PCLPointCloud2 const> pcl::PCLPointCloud2ConstPtr

Definition at line 56 of file PCLPointCloud2.h.

typedef boost::shared_ptr< ::pcl::PCLPointCloud2> pcl::PCLPointCloud2Ptr

Definition at line 55 of file PCLPointCloud2.h.

typedef boost::shared_ptr< ::pcl::PCLPointField const> pcl::PCLPointFieldConstPtr

Definition at line 42 of file PCLPointField.h.

typedef boost::shared_ptr< ::pcl::PCLPointField> pcl::PCLPointFieldPtr

Definition at line 41 of file PCLPointField.h.

typedef std::vector<PointCorrespondence3D, Eigen::aligned_allocator<PointCorrespondence3D> > pcl::PointCorrespondences3DVector

Definition at line 133 of file correspondence.h.

typedef std::vector<PointCorrespondence6D, Eigen::aligned_allocator<PointCorrespondence6D> > pcl::PointCorrespondences6DVector

Definition at line 149 of file correspondence.h.

typedef boost::shared_ptr< ::pcl::PointIndices const> pcl::PointIndicesConstPtr

Definition at line 27 of file PointIndices.h.

typedef boost::shared_ptr< ::pcl::PointIndices> pcl::PointIndicesPtr

Definition at line 26 of file PointIndices.h.

typedef boost::shared_ptr< ::pcl::PolygonMesh const> pcl::PolygonMeshConstPtr

Definition at line 33 of file PolygonMesh.h.

typedef boost::shared_ptr< ::pcl::PolygonMesh> pcl::PolygonMeshPtr

Definition at line 32 of file PolygonMesh.h.

Definition at line 129 of file polynomial_calculations.h.

Definition at line 128 of file polynomial_calculations.h.

Definition at line 231 of file multi_channel_2d_data_set.h.

Definition at line 232 of file multi_channel_2d_data_set.h.

typedef boost::shared_ptr<pcl::TextureMesh const> pcl::TextureMeshConstPtr

Definition at line 110 of file TextureMesh.h.

typedef boost::shared_ptr<pcl::TextureMesh> pcl::TextureMeshPtr

Definition at line 109 of file TextureMesh.h.

typedef Eigen::Matrix<uint8_t, 3, 1> pcl::Vector3c

Definition at line 166 of file point_types.hpp.

typedef Eigen::Map<Vector3c> pcl::Vector3cMap

Definition at line 167 of file point_types.hpp.

typedef const Eigen::Map<const Vector3c> pcl::Vector3cMapConst

Definition at line 168 of file point_types.hpp.

typedef Eigen::Map<Eigen::Vector3f> pcl::Vector3fMap

Definition at line 161 of file point_types.hpp.

typedef const Eigen::Map<const Eigen::Vector3f> pcl::Vector3fMapConst

Definition at line 162 of file point_types.hpp.

typedef Eigen::Matrix<uint8_t, 4, 1> pcl::Vector4c

Definition at line 169 of file point_types.hpp.

typedef Eigen::Map<Vector4c, Eigen::Aligned> pcl::Vector4cMap

Definition at line 170 of file point_types.hpp.

typedef const Eigen::Map<const Vector4c, Eigen::Aligned> pcl::Vector4cMapConst

Definition at line 171 of file point_types.hpp.

typedef Eigen::Map<Eigen::Vector4f, Eigen::Aligned> pcl::Vector4fMap

Definition at line 163 of file point_types.hpp.

typedef const Eigen::Map<const Eigen::Vector4f, Eigen::Aligned> pcl::Vector4fMapConst

Definition at line 164 of file point_types.hpp.

Definition at line 111 of file vector_average.h.

Definition at line 112 of file vector_average.h.

Definition at line 113 of file vector_average.h.

typedef boost::shared_ptr<Vertices const> pcl::VerticesConstPtr

Definition at line 28 of file Vertices.h.

typedef boost::shared_ptr<Vertices> pcl::VerticesPtr

Definition at line 27 of file Vertices.h.

Enumeration Type Documentation

Enumerator
BORDER_CONSTANT 
BORDER_REPLICATE 
BORDER_REFLECT 
BORDER_WRAP 
BORDER_REFLECT_101 
BORDER_TRANSPARENT 
BORDER_DEFAULT 

Definition at line 227 of file io.h.

Enumerator
MORPH_OPEN 
MORPH_CLOSE 
MORPH_DILATE 
MORPH_ERODE 

Definition at line 53 of file morphological_filter.h.

Enumerator
SACMODEL_PLANE 
SACMODEL_LINE 
SACMODEL_CIRCLE2D 
SACMODEL_CIRCLE3D 
SACMODEL_SPHERE 
SACMODEL_CYLINDER 
SACMODEL_CONE 
SACMODEL_TORUS 
SACMODEL_PARALLEL_LINE 
SACMODEL_PERPENDICULAR_PLANE 
SACMODEL_PARALLEL_LINES 
SACMODEL_NORMAL_PLANE 
SACMODEL_NORMAL_SPHERE 
SACMODEL_REGISTRATION 
SACMODEL_REGISTRATION_2D 
SACMODEL_PARALLEL_PLANE 
SACMODEL_NORMAL_PARALLEL_PLANE 
SACMODEL_STICK 

Definition at line 48 of file model_types.h.

Function Documentation

template<typename PointT >
void pcl::approximatePolygon ( const PlanarPolygon< PointT > &  polygon,
PlanarPolygon< PointT > &  approx_polygon,
float  threshold,
bool  refine = false,
bool  closed = true 
)
template<typename PointT >
void pcl::approximatePolygon2D ( const typename PointCloud< PointT >::VectorType &  polygon,
typename PointCloud< PointT >::VectorType &  approx_polygon,
float  threshold,
bool  refine = false,
bool  closed = true 
)

returns an approximate polygon to given 2D contour.

Uses just X and Y values.

Note
if refinement is not turned on, the resulting polygon will contain points from the original contour with their original z values (if any)
if refinement is turned on, the z values of the refined polygon are not valid and should be set to 0 if point contains z attribute.
Parameters
[in]polygoninput polygon
[out]approx_polygonapproximate polygon
[in]thresholdmaximum allowed distance of an input vertex to an output edge
refine
[in]closedwhether it is a closed polygon or a polyline
Author
Suat Gedikli gedik.nosp@m.li@w.nosp@m.illow.nosp@m.gara.nosp@m.ge.co.nosp@m.m

Definition at line 71 of file polygon_operations.hpp.

References pcl::PointCloud< T >::clear(), eigen22(), pcl::PointCloud< T >::push_back(), pcl::PointCloud< T >::reserve(), and pcl::PointCloud< T >::size().

template<typename Scalar >
bool pcl::checkCoordinateSystem ( const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &  line_x,
const Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > &  line_y,
const Scalar  norm_limit = 1e-3,
const Scalar  dot_limit = 1e-3 
)

Check coordinate system integrity.

Parameters
[in]line_xthe first axis
[in]line_ythe second axis
[in]norm_limitthe limit to ignore norm rounding errors
[in]dot_limitthe limit to ignore dot product rounding errors
Returns
True if the coordinate system is consistent, false otherwise.

Lines must be filled in this form:
line[0-2] = Origin coordinates of the vector
line[3-5] = Direction vector

Can be used like this :
line_x = X axis and line_y = Y axis
line_x = Z axis and line_y = X axis
line_x = Y axis and line_y = Z axis
Because X^Y = Z, Z^X = Y and Y^Z = X. Do NOT invert line order !

Determine whether a coordinate system is consistent or not by checking :
Line origins: They must be the same for the 2 lines
Norm: The 2 lines must be normalized
Dot products: Must be 0 or perpendicular vectors

Definition at line 862 of file eigen.hpp.

Referenced by transformBetween2CoordinateSystems().

bool pcl::checkCoordinateSystem ( const Eigen::Matrix< double, Eigen::Dynamic, 1 > &  line_x,
const Eigen::Matrix< double, Eigen::Dynamic, 1 > &  line_y,
const double  norm_limit = 1e-3,
const double  dot_limit = 1e-3 
)
inline

Definition at line 602 of file eigen.h.

bool pcl::checkCoordinateSystem ( const Eigen::Matrix< float, Eigen::Dynamic, 1 > &  line_x,
const Eigen::Matrix< float, Eigen::Dynamic, 1 > &  line_y,
const float  norm_limit = 1e-3,
const float  dot_limit = 1e-3 
)
inline

Definition at line 611 of file eigen.h.

template<typename Scalar >
bool pcl::checkCoordinateSystem ( const Eigen::Matrix< Scalar, 3, 1 > &  origin,
const Eigen::Matrix< Scalar, 3, 1 > &  x_direction,
const Eigen::Matrix< Scalar, 3, 1 > &  y_direction,
const Scalar  norm_limit = 1e-3,
const Scalar  dot_limit = 1e-3 
)
inline

Check coordinate system integrity.

Parameters
[in]originthe origin of the coordinate system
[in]x_directionthe first axis
[in]y_directionthe second axis
[in]norm_limitthe limit to ignore norm rounding errors
[in]dot_limitthe limit to ignore dot product rounding errors
Returns
True if the coordinate system is consistent, false otherwise.

Read the other variant for more information

Definition at line 630 of file eigen.h.

bool pcl::checkCoordinateSystem ( const Eigen::Matrix< double, 3, 1 > &  origin,
const Eigen::Matrix< double, 3, 1 > &  x_direction,
const Eigen::Matrix< double, 3, 1 > &  y_direction,
const double  norm_limit = 1e-3,
const double  dot_limit = 1e-3 
)
inline

Definition at line 644 of file eigen.h.

bool pcl::checkCoordinateSystem ( const Eigen::Matrix< float, 3, 1 > &  origin,
const Eigen::Matrix< float, 3, 1 > &  x_direction,
const Eigen::Matrix< float, 3, 1 > &  y_direction,
const float  norm_limit = 1e-3,
const float  dot_limit = 1e-3 
)
inline

Definition at line 660 of file eigen.h.

bool pcl::comparePair ( std::pair< float, int >  i,
std::pair< float, int >  j 
)
inline
template<typename PointT >
unsigned int pcl::compute3DCentroid ( ConstCloudIterator< PointT > &  cloud_iterator,
Eigen::Vector4f &  centroid 
)
inline

Definition at line 69 of file centroid.h.

template<typename PointT >
unsigned int pcl::compute3DCentroid ( ConstCloudIterator< PointT > &  cloud_iterator,
Eigen::Vector4d &  centroid 
)
inline

Definition at line 76 of file centroid.h.

template<typename PointT >
unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud,
Eigen::Vector4f &  centroid 
)
inline

Definition at line 95 of file centroid.h.

template<typename PointT >
unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud,
Eigen::Vector4d &  centroid 
)
inline

Definition at line 102 of file centroid.h.

template<typename PointT >
unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
Eigen::Vector4f &  centroid 
)
inline

Definition at line 124 of file centroid.h.

template<typename PointT >
unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
Eigen::Vector4d &  centroid 
)
inline

Definition at line 132 of file centroid.h.

template<typename PointT >
unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
Eigen::Vector4f &  centroid 
)
inline

Definition at line 155 of file centroid.h.

template<typename PointT >
unsigned int pcl::compute3DCentroid ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
Eigen::Vector4d &  centroid 
)
inline

Definition at line 163 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const Eigen::Vector4f &  centroid,
Eigen::Matrix3f &  covariance_matrix 
)
inline

Definition at line 189 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const Eigen::Vector4d &  centroid,
Eigen::Matrix3d &  covariance_matrix 
)
inline

Definition at line 197 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
const Eigen::Vector4f &  centroid,
Eigen::Matrix3f &  covariance_matrix 
)
inline

Definition at line 258 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
const Eigen::Vector4d &  centroid,
Eigen::Matrix3d &  covariance_matrix 
)
inline

Definition at line 267 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
const Eigen::Vector4f &  centroid,
Eigen::Matrix3f &  covariance_matrix 
)
inline

Definition at line 295 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
const Eigen::Vector4d &  centroid,
Eigen::Matrix3d &  covariance_matrix 
)
inline

Definition at line 304 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
Eigen::Matrix3f &  covariance_matrix 
)
inline

Definition at line 512 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
Eigen::Matrix3d &  covariance_matrix 
)
inline

Definition at line 519 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
Eigen::Matrix3f &  covariance_matrix 
)
inline

Definition at line 543 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
Eigen::Matrix3d &  covariance_matrix 
)
inline

Definition at line 551 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
Eigen::Matrix3f &  covariance_matrix 
)
inline

Definition at line 576 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
Eigen::Matrix3d &  covariance_matrix 
)
inline

Definition at line 584 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud,
const Eigen::Vector4f &  centroid,
Eigen::Matrix3f &  covariance_matrix 
)
inline

Definition at line 223 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud,
const Eigen::Vector4d &  centroid,
Eigen::Matrix3d &  covariance_matrix 
)
inline

Definition at line 231 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
const Eigen::Vector4f &  centroid,
Eigen::Matrix3f &  covariance_matrix 
)
inline

Definition at line 334 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
const Eigen::Vector4d &  centroid,
Eigen::Matrix3d &  covariance_matrix 
)
inline

Definition at line 343 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
const Eigen::Vector4f &  centroid,
Eigen::Matrix3f &  covariance_matrix 
)
inline

Definition at line 372 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeCovarianceMatrixNormalized ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
const Eigen::Vector4d &  centroid,
Eigen::Matrix3d &  covariance_matrix 
)
inline

Definition at line 381 of file centroid.h.

PCL_EXPORTS bool pcl::computeCPPFPairFeature ( const Eigen::Vector4f &  p1,
const Eigen::Vector4f &  n1,
const Eigen::Vector4i &  c1,
const Eigen::Vector4f &  p2,
const Eigen::Vector4f &  n2,
const Eigen::Vector4i &  c2,
float &  f1,
float &  f2,
float &  f3,
float &  f4,
float &  f5,
float &  f6,
float &  f7,
float &  f8,
float &  f9,
float &  f10 
)
Parameters
[in]p1
[in]n1
[in]p2
[in]n2
[in]c1
[in]c2
[out]f1
[out]f2
[out]f3
[out]f4
[out]f5
[out]f6
[out]f7
[out]f8
[out]f9
[out]f10
template<typename PointT >
unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
Eigen::Matrix3f &  covariance_matrix,
Eigen::Vector4f &  centroid 
)
inline

Definition at line 407 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
Eigen::Matrix3d &  covariance_matrix,
Eigen::Vector4d &  centroid 
)
inline

Definition at line 415 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
Eigen::Matrix3f &  covariance_matrix,
Eigen::Vector4f &  centroid 
)
inline

Definition at line 442 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
Eigen::Matrix3d &  covariance_matrix,
Eigen::Vector4d &  centroid 
)
inline

Definition at line 451 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
Eigen::Matrix3f &  covariance_matrix,
Eigen::Vector4f &  centroid 
)
inline

Definition at line 479 of file centroid.h.

template<typename PointT >
unsigned int pcl::computeMeanAndCovarianceMatrix ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
Eigen::Matrix3d &  covariance_matrix,
Eigen::Vector4d &  centroid 
)
inline

Definition at line 488 of file centroid.h.

template<typename PointT >
void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud,
Eigen::VectorXf &  centroid 
)
inline

Definition at line 883 of file centroid.h.

template<typename PointT >
void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud,
Eigen::VectorXd &  centroid 
)
inline

Definition at line 890 of file centroid.h.

template<typename PointT >
void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
Eigen::VectorXf &  centroid 
)
inline

Definition at line 909 of file centroid.h.

template<typename PointT >
void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud,
const std::vector< int > &  indices,
Eigen::VectorXd &  centroid 
)
inline

Definition at line 917 of file centroid.h.

template<typename PointT >
void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
Eigen::VectorXf &  centroid 
)
inline

Definition at line 937 of file centroid.h.

template<typename PointT >
void pcl::computeNDCentroid ( const pcl::PointCloud< PointT > &  cloud,
const pcl::PointIndices indices,
Eigen::VectorXd &  centroid 
)
inline

Definition at line 945 of file centroid.h.

PCL_EXPORTS bool pcl::computePPFPairFeature ( const Eigen::Vector4f &  p1,
const Eigen::Vector4f &  n1,
const Eigen::Vector4f &  p2,
const Eigen::Vector4f &  n2,
float &  f1,
float &  f2,
float &  f3,
float &  f4 
)
Parameters
[in]p1
[in]n1
[in]p2
[in]n2
[out]f1
[out]f2
[out]f3
[out]f4
PCL_EXPORTS bool pcl::computeRGBPairFeatures ( const Eigen::Vector4f &  p1,
const Eigen::Vector4f &  n1,
const Eigen::Vector4i &  colors1,
const Eigen::Vector4f &  p2,
const Eigen::Vector4f &  n2,
const Eigen::Vector4i &  colors2,
float &  f1,
float &  f2,
float &  f3,
float &  f4,
float &  f5,
float &  f6,
float &  f7 
)
template<typename Matrix , typename Roots >
void pcl::computeRoots ( const Matrix &  m,
Roots &  roots 
)
inline

computes the roots of the characteristic polynomial of the input matrix m, which are the eigenvalues

Parameters
[in]minput matrix
[out]rootsroots of the characteristic polynomial of the input matrix m, which are the eigenvalues

Definition at line 61 of file eigen.hpp.

References computeRoots2().

Referenced by pcl::VectorAverage< real, dimension >::doPCA(), and eigen33().

template<typename Scalar , typename Roots >
void pcl::computeRoots2 ( const Scalar &  b,
const Scalar &  c,
Roots &  roots 
)
inline

Compute the roots of a quadratic polynom x^2 + b*x + c = 0.

Parameters
[in]blinear parameter
[in]cconstant parameter
[out]rootssolutions of x^2 + b*x + c = 0

Definition at line 46 of file eigen.hpp.

Referenced by computeRoots().

template<typename Type >
void pcl::copyStringValue ( const std::string &  st,
pcl::PCLPointCloud2 cloud,
unsigned int  point_index,
unsigned int  field_idx,
unsigned int  fields_count 
)
inline

Copy one single value of type T (uchar, char, uint, int, float, double, ...) from a string.

Uses aoti/atof to do the conversion. Checks if the st is "nan" and converts it accordingly.

Parameters
[in]stthe string containing the value to convert and copy
[out]cloudthe cloud to copy it to
[in]point_indexthe index of the point
[in]field_idxthe index of the dimension/field
[in]fields_countthe current fields count

Definition at line 319 of file file_io.h.

References pcl::PCLPointCloud2::data, pcl::PCLPointCloud2::fields, pcl::PCLPointCloud2::is_dense, and pcl::PCLPointCloud2::point_step.

template<>
void pcl::copyStringValue< int8_t > ( const std::string &  st,
pcl::PCLPointCloud2 cloud,
unsigned int  point_index,
unsigned int  field_idx,
unsigned int  fields_count 
)
inline

Definition at line 342 of file file_io.h.

template<>
void pcl::copyStringValue< uint8_t > ( const std::string &  st,
pcl::PCLPointCloud2 cloud,
unsigned int  point_index,
unsigned int  field_idx,
unsigned int  fields_count 
)
inline

Definition at line 368 of file file_io.h.

template<typename Type >
void pcl::copyValueString ( const pcl::PCLPointCloud2 cloud,
const unsigned int  point_index,
const int  point_size,
const unsigned int  field_idx,
const unsigned int  fields_count,
std::ostream &  stream 
)
inline

insers a value of type Type (uchar, char, uint, int, float, double, ...) into a stringstream.

If the value is NaN, it inserst "nan".

Parameters
[in]cloudthe cloud to copy from
[in]point_indexthe index of the point
[in]point_sizethe size of the point in the cloud
[in]field_idxthe index of the dimension/field
[in]fields_countthe current fields count
[out]streamthe ostringstream to copy into

Definition at line 236 of file file_io.h.

References pcl::PCLPointCloud2::data, and pcl::PCLPointCloud2::fields.

template<>
void pcl::copyValueString< int8_t > ( const pcl::PCLPointCloud2 cloud,
const unsigned int  point_index,
const int  point_size,
const unsigned int  field_idx,
const unsigned int  fields_count,
std::ostream &  stream 
)
inline

Definition at line 251 of file file_io.h.

template<>
void pcl::copyValueString< uint8_t > ( const pcl::PCLPointCloud2 cloud,
const unsigned int  point_index,
const int  point_size,
const unsigned int  field_idx,
const unsigned int  fields_count,
std::ostream &  stream 
)
inline

Definition at line 267 of file file_io.h.

template<typename PointT >
void pcl::createMapping ( const std::vector< pcl::PCLPointField > &  msg_fields,
MsgFieldMap &  field_map 
)

Definition at line 125 of file conversions.h.

References pcl::detail::fieldOrdering().

template<typename PointT >
void pcl::demeanPointCloud ( ConstCloudIterator< PointT > &  cloud_iterator,
const Eigen::Vector4f &  centroid,
pcl::PointCloud< PointT > &  cloud_out,
int  npts = 0 
)

Definition at line 605 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( ConstCloudIterator< PointT > &  cloud_iterator,
const Eigen::Vector4d &  centroid,
pcl::PointCloud< PointT > &  cloud_out,
int  npts = 0 
)

Definition at line 614 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( ConstCloudIterator< PointT > &  cloud_iterator,
const Eigen::Vector4f &  centroid,
pcl::PointCloud< PointT > &  cloud_out 
)

Definition at line 634 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( ConstCloudIterator< PointT > &  cloud_iterator,
const Eigen::Vector4d &  centroid,
pcl::PointCloud< PointT > &  cloud_out 
)

Definition at line 642 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( const pcl::PointCloud< PointT > &  cloud_in,
const std::vector< int > &  indices,
const Eigen::Vector4f &  centroid,
pcl::PointCloud< PointT > &  cloud_out 
)

Definition at line 663 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( const pcl::PointCloud< PointT > &  cloud_in,
const std::vector< int > &  indices,
const Eigen::Vector4d &  centroid,
pcl::PointCloud< PointT > &  cloud_out 
)

Definition at line 672 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( const pcl::PointCloud< PointT > &  cloud_in,
const pcl::PointIndices indices,
const Eigen::Vector4f &  centroid,
pcl::PointCloud< PointT > &  cloud_out 
)

Definition at line 694 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( const pcl::PointCloud< PointT > &  cloud_in,
const pcl::PointIndices indices,
const Eigen::Vector4d &  centroid,
pcl::PointCloud< PointT > &  cloud_out 
)

Definition at line 703 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( ConstCloudIterator< PointT > &  cloud_iterator,
const Eigen::Vector4f &  centroid,
Eigen::MatrixXf &  cloud_out,
int  npts = 0 
)

Definition at line 727 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( ConstCloudIterator< PointT > &  cloud_iterator,
const Eigen::Vector4d &  centroid,
Eigen::MatrixXd &  cloud_out,
int  npts = 0 
)

Definition at line 736 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( const pcl::PointCloud< PointT > &  cloud_in,
const Eigen::Vector4f &  centroid,
Eigen::MatrixXf &  cloud_out 
)

Definition at line 758 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( const pcl::PointCloud< PointT > &  cloud_in,
const Eigen::Vector4d &  centroid,
Eigen::MatrixXd &  cloud_out 
)

Definition at line 766 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( const pcl::PointCloud< PointT > &  cloud_in,
const std::vector< int > &  indices,
const Eigen::Vector4f &  centroid,
Eigen::MatrixXf &  cloud_out 
)

Definition at line 789 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( const pcl::PointCloud< PointT > &  cloud_in,
const std::vector< int > &  indices,
const Eigen::Vector4d &  centroid,
Eigen::MatrixXd &  cloud_out 
)

Definition at line 798 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( const pcl::PointCloud< PointT > &  cloud_in,
const pcl::PointIndices indices,
const Eigen::Vector4f &  centroid,
Eigen::MatrixXf &  cloud_out 
)

Definition at line 822 of file centroid.h.

template<typename PointT >
void pcl::demeanPointCloud ( const pcl::PointCloud< PointT > &  cloud_in,
const pcl::PointIndices indices,
const Eigen::Vector4d &  centroid,
Eigen::MatrixXd &  cloud_out 
)

Definition at line 831 of file centroid.h.

template<typename PointT >
double pcl::estimateProjectionMatrix ( typename pcl::PointCloud< PointT >::ConstPtr  cloud,
Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &  projection_matrix,
const std::vector< int > &  indices = std::vector<int> () 
)

Estimates the projection matrix P = K * (R|-R*t) from organized point clouds, with K = [[fx, s, cx], [0, fy, cy], [0, 0, 1]] R = rotation matrix and t = translation vector.

Parameters
[in]cloudinput cloud. Must be organized and from a projective device. e.g. stereo or kinect, ...
[out]projection_matrixoutput projection matrix
[in]indicesThe indices to be used to determine the projection matrix
Returns
the resudial error. A high residual indicates, that the point cloud was not from a projective device.

Definition at line 78 of file projection_matrix.hpp.

References B, pcl::ConstCloudIterator< PointT >::getCurrentPointIndex(), pcl::PointCloud< T >::height, pcl::common::internal::makeSymmetric(), and pcl::PointCloud< T >::width.

template<typename PointType1 , typename PointType2 >
float pcl::euclideanDistance ( const PointType1 &  p1,
const PointType2 &  p2 
)
inline
template<typename Sequence , typename F >
void pcl::for_each_type ( f)
inline

Definition at line 93 of file for_each_type.h.

template<typename PointT >
void pcl::fromPCLPointCloud2 ( const pcl::PCLPointCloud2 msg,
pcl::PointCloud< PointT > &  cloud,
const MsgFieldMap &  field_map 
)

Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.

Parameters
[in]msgthe PCLPointCloud2 binary blob
[out]cloudthe resultant pcl::PointCloud<T>
[in]field_mapa MsgFieldMap object
Note
Use fromPCLPointCloud2 (PCLPointCloud2, PointCloud<T>) directly or create you own MsgFieldMap using:
MsgFieldMap field_map;
createMapping<PointT> (msg.fields, field_map);

Definition at line 169 of file conversions.h.

References pcl::PCLPointCloud2::data, pcl::PCLPointCloud2::header, pcl::PointCloud< T >::header, pcl::PCLPointCloud2::height, pcl::PointCloud< T >::height, pcl::PCLPointCloud2::is_dense, pcl::PointCloud< T >::is_dense, pcl::PCLPointCloud2::point_step, pcl::PointCloud< T >::points, pcl::PCLPointCloud2::row_step, pcl::detail::FieldMapping::serialized_offset, pcl::detail::FieldMapping::size, pcl::detail::FieldMapping::struct_offset, pcl::PCLPointCloud2::width, and pcl::PointCloud< T >::width.

Referenced by fromPCLPointCloud2(), fromROSMsg(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::getMeshesFromTSDFVector(), pcl::TextureMapping< PointInT >::mapMultipleTexturesToMeshUV(), pcl::PCDGrabber< PointT >::operator[](), pcl::ImageGrabber< PointT >::operator[](), pcl::StereoGrabber< PointT >::publish(), pcl::PCDGrabber< PointT >::publish(), pcl::ImageGrabber< PointT >::publish(), pcl::outofcore::OutofcoreOctreeBaseNode< ContainerT, PointT >::queryBBIncludes(), pcl::IFSReader::read(), pcl::FileReader::read(), pcl::PLYReader::read(), pcl::OBJReader::read(), pcl::PCDReader::read(), pcl::TextureMapping< PointInT >::removeOccludedPoints(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::runMarchingCubes(), pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setSourceNormals(), pcl::registration::CorrespondenceEstimationNormalShooting< PointSource, PointTarget, NormalT, Scalar >::setSourceNormals(), pcl::registration::CorrespondenceRejectorSurfaceNormal::setSourceNormals(), pcl::registration::CorrespondenceRejectionOrganizedBoundary::setSourcePoints(), pcl::registration::CorrespondenceRejectorMedianDistance::setSourcePoints(), pcl::registration::CorrespondenceRejectorPoly< SourceT, TargetT >::setSourcePoints(), pcl::registration::CorrespondenceRejectorVarTrimmed::setSourcePoints(), pcl::registration::CorrespondenceRejectorDistance::setSourcePoints(), pcl::registration::CorrespondenceRejectorSampleConsensus< PointT >::setSourcePoints(), pcl::registration::CorrespondenceRejectorSurfaceNormal::setSourcePoints(), pcl::registration::CorrespondenceEstimationBackProjection< PointSource, PointTarget, NormalT, Scalar >::setTargetNormals(), pcl::registration::CorrespondenceRejectorSurfaceNormal::setTargetNormals(), pcl::registration::CorrespondenceRejectionOrganizedBoundary::setTargetPoints(), pcl::registration::CorrespondenceRejectorPoly< SourceT, TargetT >::setTargetPoints(), pcl::registration::CorrespondenceRejectorMedianDistance::setTargetPoints(), pcl::registration::CorrespondenceRejectorVarTrimmed::setTargetPoints(), pcl::registration::CorrespondenceRejectorDistance::setTargetPoints(), pcl::registration::CorrespondenceRejectorSampleConsensus< PointT >::setTargetPoints(), pcl::registration::CorrespondenceRejectorSurfaceNormal::setTargetPoints(), pcl::TextureMapping< PointInT >::showOcclusions(), pcl::TextureMapping< PointInT >::sortFacesByCamera(), pcl::TextureMapping< PointInT >::textureMeshwithMultipleCameras(), and pcl::geometry::toHalfEdgeMesh().

template<typename PointT >
void pcl::fromPCLPointCloud2 ( const pcl::PCLPointCloud2 msg,
pcl::PointCloud< PointT > &  cloud 
)

Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object.

Parameters
[in]msgthe PCLPointCloud2 binary blob
[out]cloudthe resultant pcl::PointCloud<T>

Definition at line 230 of file conversions.h.

References pcl::PCLPointCloud2::fields, and fromPCLPointCloud2().

template<typename PointT >
void pcl::fromROSMsg ( const pcl::PCLPointCloud2 msg,
pcl::PointCloud< PointT > &  cloud,
const MsgFieldMap &  field_map 
)

Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.

Parameters
[in]msgthe PCLPointCloud2 binary blob
[out]cloudthe resultant pcl::PointCloud<T>
[in]field_mapa MsgFieldMap object
Note
Use fromROSMsg (PCLPointCloud2, PointCloud<T>) directly or create you own MsgFieldMap using:
MsgFieldMap field_map;
createMapping<PointT> (msg.fields, field_map);

Definition at line 68 of file conversions.h.

References fromPCLPointCloud2().

template<typename PointT >
void pcl::fromROSMsg ( const pcl::PCLPointCloud2 msg,
pcl::PointCloud< PointT > &  cloud 
)

Convert a PCLPointCloud2 binary data blob into a pcl::PointCloud<T> object.

Parameters
[in]msgthe PCLPointCloud2 binary blob
[out]cloudthe resultant pcl::PointCloud<T>

Definition at line 81 of file conversions.h.

References fromPCLPointCloud2().

void pcl::getAllPcdFilesInDirectory ( const std::string &  directory,
std::vector< std::string > &  file_names 
)
inline

Find all *.pcd files in the directory and return them sorted.

Parameters
directorythe directory to be searched
file_namesthe resulting (sorted) list of .pcd files

Definition at line 46 of file file_io.hpp.

PCL_EXPORTS void pcl::getCameraMatrixFromProjectionMatrix ( const Eigen::Matrix< float, 3, 4, Eigen::RowMajor > &  projection_matrix,
Eigen::Matrix3f &  camera_matrix 
)

Determines the camera matrix from the given projection matrix.

Note
This method does NOT use a RQ decomposition, but uses the fact that the left 3x3 matrix P' of P squared eliminates the rotational part. P' = K * R -> P' * P'^T = K * R * R^T * K = K * K^T
Parameters
[in]projection_matrix
[out]camera_matrix

Referenced by pcl::search::OrganizedNeighbor< PointT >::computeCameraMatrix().

void pcl::getEulerAngles ( const Eigen::Affine3f &  t,
float &  roll,
float &  pitch,
float &  yaw 
)
inline

Definition at line 269 of file eigen.h.

void pcl::getEulerAngles ( const Eigen::Affine3d &  t,
double &  roll,
double &  pitch,
double &  yaw 
)
inline

Definition at line 275 of file eigen.h.

PCL_EXPORTS void pcl::getFieldsSizes ( const std::vector< pcl::PCLPointField > &  fields,
std::vector< int > &  field_sizes 
)

Obtain a vector with the sizes of all valid fields (e.g., not "_")

Parameters
[in]fieldsthe input vector containing the fields
[out]field_sizesthe resultant field sizes in bytes
template<typename PointT , typename ValT >
void pcl::getFieldValue ( const PointT pt,
size_t  field_offset,
ValT &  value 
)
inline

Get the value at a specified field in a point.

Parameters
[in]ptthe point to get the value from
[in]field_offsetthe offset of the field
[out]valuethe value to retreive

Definition at line 343 of file point_traits.h.

std::string pcl::getFileExtension ( const std::string &  input)
inline

Get the file extension from the given string (the remaining string after the last '.

')

Parameters
inputthe input filename
Returns
input 's file extension

Definition at line 81 of file file_io.hpp.

std::string pcl::getFilenameWithoutExtension ( const std::string &  input)
inline

Remove the extension from the given string and return only the filename (everything before the last '.

')

Parameters
inputthe input filename (with the file extension)
Returns
the resulting filename, stripped of its extension

Definition at line 75 of file file_io.hpp.

std::string pcl::getFilenameWithoutPath ( const std::string &  input)
inline

Remove the path from the given string and return only the filename (the remaining string after the last '/')

Parameters
inputthe input filename (with full path)
Returns
the resulting filename, stripped of the path

Definition at line 69 of file file_io.hpp.

template<typename PointT >
float pcl::getMeanPointDensity ( const typename pcl::PointCloud< PointT >::ConstPtr &  cloud,
float  max_dist,
int  nr_threads = 1 
)
inline

Compute the mean point density of a given point cloud.

Parameters
[in]cloudpointer to the input point cloud
[in]max_distmaximum distance of a point to be considered as a neighbor
[in]nr_threadsnumber of threads to use (default = 1, only used if OpenMP flag is set)
Returns
the mean point density of a given point cloud

Definition at line 49 of file ia_fpcs.hpp.

References pcl::search::KdTree< PointT, Tree >::nearestKSearch(), pcl::PointCloud< T >::points, pcl::search::KdTree< PointT, Tree >::setInputCloud(), and pcl::PointCloud< T >::size().

template<typename PointT >
float pcl::getMeanPointDensity ( const typename pcl::PointCloud< PointT >::ConstPtr &  cloud,
const std::vector< int > &  indices,
float  max_dist,
int  nr_threads = 1 
)
inline

Compute the mean point density of a given point cloud.

Parameters
[in]cloudpointer to the input point cloud
[in]indicesthe vector of point indices to use from cloud
[in]max_distmaximum distance of a point to be considered as a neighbor
[in]nr_threadsnumber of threads to use (default = 1, only used if OpenMP flag is set)
Returns
the mean point density of a given point cloud

Definition at line 85 of file ia_fpcs.hpp.

References pcl::search::KdTree< PointT, Tree >::nearestKSearch(), pcl::PointCloud< T >::points, and pcl::search::KdTree< PointT, Tree >::setInputCloud().

PCL_EXPORTS void pcl::getMinMax3D ( const pcl::PCLPointCloud2ConstPtr cloud,
int  x_idx,
int  y_idx,
int  z_idx,
Eigen::Vector4f &  min_pt,
Eigen::Vector4f &  max_pt 
)

Obtain the maximum and minimum points in 3D from a given point cloud.

Parameters
[in]cloudthe pointer to a pcl::PCLPointCloud2 dataset
[in]x_idxthe index of the X channel
[in]y_idxthe index of the Y channel
[in]z_idxthe index of the Z channel
[out]min_ptthe minimum data point
[out]max_ptthe maximum data point
PCL_EXPORTS void pcl::getMinMax3D ( const pcl::PCLPointCloud2ConstPtr cloud,
int  x_idx,
int  y_idx,
int  z_idx,
const std::string &  distance_field_name,
float  min_distance,
float  max_distance,
Eigen::Vector4f &  min_pt,
Eigen::Vector4f &  max_pt,
bool  limit_negative = false 
)

Obtain the maximum and minimum points in 3D from a given point cloud.

Note
Performs internal data filtering as well.
Parameters
[in]cloudthe pointer to a pcl::PCLPointCloud2 dataset
[in]x_idxthe index of the X channel
[in]y_idxthe index of the Y channel
[in]z_idxthe index of the Z channel
[in]distance_field_namethe name of the dimension to filter data along to
[in]min_distancethe minimum acceptable value in distance_field_name data
[in]max_distancethe maximum acceptable value in distance_field_name data
[out]min_ptthe minimum data point
[out]max_ptthe maximum data point
[in]limit_negativefalse if data inside of the [min_distance; max_distance] interval should be considered, true otherwise.
template<typename PointT , typename Scalar >
double pcl::getPrincipalTransformation ( const pcl::PointCloud< PointT > &  cloud,
Eigen::Transform< Scalar, 3, Eigen::Affine > &  transform 
)
inline

Calculates the principal (PCA-based) alignment of the point cloud.

Parameters
[in]cloudthe input point cloud
[out]transformthe resultant transform
Returns
the ratio lambda1/lambda2 or lambda2/lambda3, whatever is closer to 1.
Note
If the return value is close to one then the transformation might be not unique -> two principal directions have almost same variance (extend)

Definition at line 338 of file transforms.hpp.

References computeMeanAndCovarianceMatrix(), eigen33(), and EIGEN_ALIGN16.

template<typename PointT >
double pcl::getPrincipalTransformation ( const pcl::PointCloud< PointT > &  cloud,
Eigen::Affine3f &  transform 
)
inline

Definition at line 491 of file transforms.h.

PCL_EXPORTS RGB pcl::getRandomColor ( double  min = 0.2,
double  max = 2.8 
)
void pcl::getRejectedQueryIndices ( const pcl::Correspondences correspondences_before,
const pcl::Correspondences correspondences_after,
std::vector< int > &  indices,
bool  presorting_required = true 
)

Get the query points of correspondences that are present in one correspondence vector but not in the other, e.g., to compare correspondences before and after rejection.

Parameters
[in]correspondences_beforeVector of correspondences before rejection
[in]correspondences_afterVector of correspondences after rejection
[out]indicesQuery point indices of correspondences that have been rejected
[in]presorting_requiredEnable/disable internal sorting of vectors. By default (true), vectors are internally sorted before determining their difference. If the order of correspondences in correspondences_after is not different (has not been changed) from the order in correspondences_before this pre-processing step can be disabled in order to gain efficiency. In order to disable pre-sorting set presorting_requered to false.

Referenced by pcl::registration::CorrespondenceRejector::getRejectedQueryIndices().

double pcl::getTime ( )
inline
void pcl::getTransformation ( float  x,
float  y,
float  z,
float  roll,
float  pitch,
float  yaw,
Eigen::Affine3f &  t 
)
inline

Definition at line 326 of file eigen.h.

void pcl::getTransformation ( double  x,
double  y,
double  z,
double  roll,
double  pitch,
double  yaw,
Eigen::Affine3d &  t 
)
inline

Definition at line 333 of file eigen.h.

void pcl::getTranslationAndEulerAngles ( const Eigen::Affine3f &  t,
float &  x,
float &  y,
float &  z,
float &  roll,
float &  pitch,
float &  yaw 
)
inline

Definition at line 296 of file eigen.h.

void pcl::getTranslationAndEulerAngles ( const Eigen::Affine3d &  t,
double &  x,
double &  y,
double &  z,
double &  roll,
double &  pitch,
double &  yaw 
)
inline

Definition at line 304 of file eigen.h.

PCL_EXPORTS int pcl::interpolatePointIndex ( int  p,
int  length,
InterpolationType  type 
)
Returns
the right index according to the interpolation type.
Note
this is adapted from OpenCV
Parameters
pthe index of point to interpolate
lengththe top/bottom row or left/right column index
typethe requested interpolation
Exceptions
pcl::BadArgumentExceptionif type is unknown

Referenced by copyPointCloud().

template<typename PointT >
bool pcl::isFinite ( const PointT pt)
inline

Tests if the 3D components of a point are all finite param[in] pt point to be tested return true if finite, false otherwise.

Definition at line 54 of file point_tests.h.

Referenced by pcl::octree::OctreePointCloudAdjacency< PointT, LeafContainerT, BranchContainerT >::addPointIdx(), pcl::octree::OctreePointCloudAdjacency< PointT, LeafContainerT, BranchContainerT >::addPointsFromInputCloud(), pcl::octree::OctreePointCloud< PointT, LeafContainerT, BranchContainerT, OctreeT >::addPointsFromInputCloud(), pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::io::OrganizedPointCloudCompression< PointT >::analyzeOrganizedCloud(), pcl::MedianFilter< PointT >::applyFilter(), pcl::CropBox< PointT >::applyFilter(), pcl::LocalMaximum< PointT >::applyFilterIndices(), pcl::ModelOutlierRemoval< PointT >::applyFilterIndices(), pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::approxNearestSearch(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::bilinearInterpolation(), pcl::filters::Pyramid< PointT >::compute(), compute3DCentroid(), pcl::GrabCut< PointT >::computeBetaNonOrganized(), computeCentroid(), computeCovarianceMatrix(), pcl::IntensityGradientEstimation< PointInT, PointNT, PointOutT, IntensitySelectorT >::computeFeature(), pcl::MomentInvariantsEstimation< PointInT, PointOutT >::computeFeature(), pcl::PrincipalCurvaturesEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SHOTEstimationOMP< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::UniqueShapeContext< PointInT, PointOutT, PointRFT >::computeFeature(), pcl::BoundaryEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::ShapeContext3DEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SHOTColorEstimationOMP< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::FPFHEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::SHOTEstimation< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), pcl::NormalEstimation< PointInT, PointOutT >::computeFeature(), pcl::SHOTColorEstimation< PointInT, PointNT, PointOutT, PointRFT >::computeFeature(), computeMeanAndCovarianceMatrix(), pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computePointPFHSignature(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::filters::Convolution3D< PointIn, PointOut, KernelT >::convolve(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::TrajkovicKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::registration::CorrespondenceEstimationOrganizedProjection< PointSource, PointTarget, Scalar >::determineCorrespondences(), pcl::RangeImage::doZBuffer(), pcl::io::PointCloudImageExtractor< PointT >::extract(), pcl::io::PointCloudImageExtractorFromLabelField< PointT >::extractImpl(), pcl::RegionGrowing< PointT, NormalT >::findPointNeighbours(), pcl::octree::OctreePointCloudAdjacency< PointT, LeafContainerT, BranchContainerT >::genOctreeKeyforPoint(), pcl::ISSKeypoint3D< PointInT, PointOutT, NormalT >::getBoundaryPoints(), pcl::visualization::PointCloudColorHandlerLabelField< PointT >::getColor(), getPointCloudDifference(), pcl::OrganizedFastMesh< PointInT >::isValidQuad(), pcl::OrganizedFastMesh< PointInT >::isValidTriangle(), pcl::search::BruteForce< PointT >::nearestKSearch(), pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::nearestKSearch(), pcl::search::OrganizedNeighbor< PointT >::nearestKSearch(), pcl::filters::GaussianKernel< PointInT, PointOutT >::operator()(), pcl::filters::GaussianKernelRGB< PointInT, PointOutT >::operator()(), pcl::OrganizedFastMesh< PointInT >::performReconstruction(), pcl::io::pointCloudTovtkStructuredGrid(), pcl::search::BruteForce< PointT >::radiusSearch(), pcl::search::OrganizedNeighbor< PointT >::radiusSearch(), pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::radiusSearch(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseHarris(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseHarris(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseLowe(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseLowe(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseNoble(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseNoble(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::responseTomasi(), pcl::HarrisKeypoint2D< PointInT, PointOutT, IntensityT >::responseTomasi(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::responseTomasi(), pcl::octree::OctreePointCloudOccupancy< PointT, LeafContainerT, BranchContainerT >::setOccupiedVoxelsAtPointsFromCloud(), pcl::visualization::PCLVisualizer::updatePointCloud(), pcl::visualization::PCLVisualizer::updatePolygonMesh(), and pcl::octree::OctreePointCloudSearch< PointT, LeafContainerT, BranchContainerT >::voxelSearch().

template<>
bool pcl::isFinite< pcl::Axis > ( const pcl::Axis )
inline

Definition at line 69 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::BorderDescription > ( const pcl::BorderDescription p)
inline

Definition at line 100 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::Boundary > ( const pcl::Boundary )
inline

Definition at line 73 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::BRISKSignature512 > ( const pcl::BRISKSignature512 )
inline

Definition at line 89 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::ESFSignature640 > ( const pcl::ESFSignature640 )
inline

Definition at line 87 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::FPFHSignature33 > ( const pcl::FPFHSignature33 )
inline

Definition at line 85 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::Intensity > ( const pcl::Intensity )
inline

Definition at line 70 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::IntensityGradient > ( const pcl::IntensityGradient )
inline

Definition at line 88 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::Label > ( const pcl::Label )
inline

Definition at line 68 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::MomentInvariants > ( const pcl::MomentInvariants )
inline

Definition at line 71 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::Normal > ( const pcl::Normal n)
inline

Definition at line 107 of file point_tests.h.

Definition at line 84 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::PFHRGBSignature250 > ( const pcl::PFHRGBSignature250 )
inline

Definition at line 81 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::PFHSignature125 > ( const pcl::PFHSignature125 )
inline

Definition at line 80 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::PointXY > ( const pcl::PointXY p)
inline

Definition at line 93 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::PPFRGBSignature > ( const pcl::PPFRGBSignature )
inline

Definition at line 83 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::PPFSignature > ( const pcl::PPFSignature )
inline

Definition at line 82 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::PrincipalCurvatures > ( const pcl::PrincipalCurvatures )
inline

Definition at line 74 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::PrincipalRadiiRSD > ( const pcl::PrincipalRadiiRSD )
inline

Definition at line 72 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::ReferenceFrame > ( const pcl::ReferenceFrame )
inline

Definition at line 77 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::RGB > ( const pcl::RGB )
inline

Definition at line 67 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::ShapeContext1980 > ( const pcl::ShapeContext1980 )
inline

Definition at line 78 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::SHOT1344 > ( const pcl::SHOT1344 )
inline

Definition at line 76 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::SHOT352 > ( const pcl::SHOT352 )
inline

Definition at line 75 of file point_tests.h.

Definition at line 79 of file point_tests.h.

template<>
bool pcl::isFinite< pcl::VFHSignature308 > ( const pcl::VFHSignature308 )
inline

Definition at line 86 of file point_tests.h.

template<typename Point1T , typename Point2T >
bool pcl::isSamePointType ( )
inline

Check if two given point types are the same or not.

Definition at line 292 of file io.h.

template<typename Type >
bool pcl::isValueFinite ( const pcl::PCLPointCloud2 cloud,
const unsigned int  point_index,
const int  point_size,
const unsigned int  field_idx,
const unsigned int  fields_count 
)
inline

Check whether a given value of type Type (uchar, char, uint, int, float, double, ...) is finite or not.

Parameters
[in]cloudthe cloud that contains the data
[in]point_indexthe index of the point
[in]point_sizethe size of the point in the cloud
[in]field_idxthe index of the dimension/field
[in]fields_countthe current fields count
Returns
true if the value is finite, false otherwise

Definition at line 294 of file file_io.h.

References pcl::PCLPointCloud2::data, and pcl::PCLPointCloud2::fields.

PCL_EXPORTS unsigned int pcl::lzfCompress ( const void *const  in_data,
unsigned int  in_len,
void *  out_data,
unsigned int  out_len 
)

Compress in_len bytes stored at the memory block starting at in_data and write the result to out_data, up to a maximum length of out_len bytes using Marc Lehmann's LZF algorithm.

If the output buffer is not large enough or any error occurs return 0, otherwise return the number of bytes used, which might be considerably more than in_len (but less than 104% of the original size), so it makes sense to always use out_len == in_len - 1), to ensure some compression, and store the data uncompressed otherwise (with a flag, of course.

Note
The buffers must not be overlapping.
Parameters
[in]in_datathe input uncompressed buffer
[in]in_lenthe length of the input buffer
[out]out_datathe output buffer where the compressed result will be stored
[out]out_lenthe length of the output buffer

Referenced by pcl::PCDWriter::writeBinaryCompressed().

PCL_EXPORTS unsigned int pcl::lzfDecompress ( const void *const  in_data,
unsigned int  in_len,
void *  out_data,
unsigned int  out_len 
)

Decompress data compressed with the lzfCompress function and stored at location in_data and length in_len.

The result will be stored at out_data up to a maximum of out_len characters.

If the output buffer is not large enough to hold the decompressed data, a 0 is returned and errno is set to E2BIG. Otherwise the number of de