Namespaces | Classes | Typedefs | Enumerations | Functions | Variables

pcl Namespace Reference

Software License Agreement (BSD License). More...

Namespaces

namespace  ComparisonOps
namespace  console
namespace  detail
namespace  fields
namespace  io
namespace  octree
namespace  registration
namespace  surface
namespace  traits
namespace  visualization

Classes

class  NNClassification
 Nearest neighbor search based classification of PCL point type features. More...
class  VFHClassifierNN
 Utility class for nearest neighbor search based classification of VFH features. 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...
struct  NdConcatenateFunctor
 Helper functor structure for concatenate. More...
class  PCA
 Principal Component analysis (PCA) class. More...
class  PiecewiseLinearFunction
 This provides functionalities to efficiently return values for piecewise linear function. More...
struct  PointCorrespondence
 Representation of a (possible) correspondence between two points in two different coordinate frames (e.g. 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  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  Synchronizer
 /brief This template class synchronizes two data streams of different types. More...
class  ScopeTime
 Class to measure the time spent in a scope. 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...
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 PointCloud2 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...
struct  _PointXYZ
struct  PointXYZ
 A point structure representing Euclidean xyz coordinates. More...
struct  RGB
 A structure representing RGB color information. More...
struct  PointXYZI
 A point structure representing Euclidean xyz coordinates, and the intensity value. More...
struct  PointXYZRGBA
 A point structure representing Euclidean xyz coordinates, and the RGBA color. More...
struct  _PointXYZRGB
struct  PointXYZRGB
 A point structure representing Euclidean xyz coordinates, and the RGB color. More...
struct  PointXY
 A 2D point structure representing Euclidean xy coordinates. More...
struct  InterestPoint
 A point structure representing an interest point with Euclidean xyz coordinates, and an interest value. More...
struct  Normal
 A point structure representing normal coordinates and the surface curvature estimate. More...
struct  PointNormal
 A point structure representing Euclidean xyz coordinates, together with normal coordinates and the surface curvature estimate. More...
struct  _PointXYZRGBNormal
 A point structure representing Euclidean xyz coordinates, and the RGB color, together with normal coordinates and the surface curvature estimate. More...
struct  PointXYZRGBNormal
struct  PointXYZINormal
 A point structure representing Euclidean xyz coordinates, intensity, together with normal coordinates and the surface curvature estimate. More...
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  PPFSignature
 A point structure for storing the Point Pair Feature (PPF) values. More...
struct  NormalBasedSignature12
 A point structure representing the Normal Based Signature for a feature matrix of 4-by-3. More...
struct  SHOT
 A point structure representing the generic Signature of Histograms of OrienTations (SHOT). More...
struct  FPFHSignature33
 A point structure representing the Signature of Histograms of OrienTations (SHOT). More...
struct  VFHSignature308
 A point structure representing the Viewpoint Feature Histogram (VFH). 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
 A point structure representing a 3-D position and scale. More...
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  ModelCoefficients
class  PCLBase
 PCL base class. More...
class  PCLBase< sensor_msgs::PointCloud2 >
class  PointCloud
 PointCloud represents a templated PointCloud implementation. 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  DefaultPointRepresentation< PointXYZ >
class  DefaultPointRepresentation< PointXYZI >
class  DefaultPointRepresentation< PointNormal >
class  DefaultPointRepresentation< PFHSignature125 >
class  DefaultPointRepresentation< FPFHSignature33 >
class  DefaultPointRepresentation< VFHSignature308 >
class  DefaultPointRepresentation< NormalBasedSignature12 >
class  CustomPointRepresentation
 CustomPointRepresentation extends PointRepresentation to allow for sub-part selection on the point. More...
struct  PointIndices
struct  PolygonMesh
struct  for_each_type_impl
struct  for_each_type_impl< false >
struct  intersect
struct  TexMaterial
struct  TextureMesh
struct  Vertices
 Describes a set of vertices in a polygon mesh, by basically storing an array of indices. More...
class  BoundaryEstimation
 BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle criterion. More...
class  CVFHEstimation
 CVFHEstimation estimates the Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset containing points and normals. More...
class  Feature
 Feature represents the base feature class. More...
class  FeatureFromNormals
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  IntegralImage2D
 Generic implementation for creating 2D integral images (including second order integral images). More...
class  IntegralImageNormalEstimation
 Surface normal estimation on dense 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  MomentInvariantsEstimation
 MomentInvariantsEstimation estimates the 3 moment invariants (j1, j2, j3) at each 3D point. 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 More...
class  NormalEstimation
 NormalEstimation estimates local surface properties at each 3D point, such as surface normals and curvatures. 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  PFHEstimation
 PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals. More...
class  PPFEstimation
 Class that calculates the "surflet" features for each pair in the given pointcloud. More...
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  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  SHOTEstimation< pcl::PointXYZRGBA, PointNT, PointOutT >
 SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals. More...
class  SHOTEstimationOMP
 SHOTEstimation 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  SHOTEstimationOMP< pcl::PointXYZRGBA, PointNT, PointOutT >
class  StatisticalMultiscaleInterestRegionExtraction
class  VFHEstimation
 VFHEstimation estimates the Viewpoint Feature Histogram (VFH) descriptor for a given point cloud dataset containing points and normals. 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  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  ExtractIndices
 ExtractIndices extracts a set of indices from a PointCloud as a separate PointCloud. More...
class  ExtractIndices< sensor_msgs::PointCloud2 >
 ExtractIndices extracts a set of indices from a PointCloud as a separate PointCloud. More...
class  Filter
 Filter represents the base filter class. More...
class  Filter< sensor_msgs::PointCloud2 >
 Filter represents the base filter class. More...
class  PassThrough
 PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints. More...
class  PassThrough< sensor_msgs::PointCloud2 >
 PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints. 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< sensor_msgs::PointCloud2 >
 ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More...
class  RadiusOutlierRemoval
 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  RadiusOutlierRemoval< sensor_msgs::PointCloud2 >
 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  StatisticalOutlierRemoval
 StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More...
class  StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >
 StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data. More...
struct  NdCopyEigenPointFunctor
 Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More...
struct  NdCopyPointEigenFunctor
 Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More...
class  VoxelGrid
 VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
class  VoxelGrid< sensor_msgs::PointCloud2 >
 VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
class  AdaptiveRangeCoder
 AdaptiveRangeCoder compression class More...
class  StaticRangeCoder
 StaticRangeCoder compression class 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  ONIGrabber
class  OpenNIGrabber
 /brief /ingroup io 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  PCLIOException
 /brief /ingroup io More...
class  PLYReader
 Point Cloud Data (PLY) file format reader. More...
class  PLYWriter
 Point Cloud Data (PLY) file format writer. More...
class  KdTree
 KdTree represents the base spatial locator class for nearest neighbor estimation. More...
class  KdTreeFLANN
 KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. More...
class  OrganizedDataIndex
 OrganizedDataIndex is a type of spatial locator used to query organized datasets, such as point clouds acquired using dense stereo devices. More...
class  OrganizedNeighborSearch
 OrganizedNeighborSearch class More...
class  Keypoint
 Keypoint represents the base class for key points. More...
class  NarfKeypoint
 NARF (Normal Aligned Radial Feature) keypoints. More...
struct  SIFTKeypointFieldSelector
struct  SIFTKeypointFieldSelector< PointNormal >
struct  SIFTKeypointFieldSelector< PointXYZRGB >
class  SIFTKeypoint
 SIFTKeypoint detects the Scale Invariant Feature Transform keypoints for a given point cloud dataset containing points and intensity. More...
class  UniformSampling
 UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. 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  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  IterativeClosestPointNonLinear
 IterativeClosestPointNonLinear is an ICP variant that uses Levenberg-Marquardt optimization backend. 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. More...
class  WarpPointRigid
class  WarpPointRigid3D
class  WarpPointRigid6D
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...
class  SampleConsensusModelCircle2D
 SampleConsensusModelCircle2D defines a model for 2D circle segmentation on the X-Y plane. 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  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  SampleConsensusModelSphere
 SampleConsensusModelSphere defines a model for 3D sphere segmentation. More...
class  SampleConsensusModelStick
 SampleConsensusModelStick defines a model for 3D stick segmentation. More...
class  EuclideanClusterExtraction
 EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense. 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  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  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  ConcaveHull
 ConcaveHull (alpha shapes) using libqhull library. More...
class  ConvexHull
 ConvexHull using libqhull library. 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  MarchingCubesGreedy
 The marching cubes surface reconstruction algorithm, using a "greedy" voxelization algorithm. 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  SurfaceReconstruction
 SurfaceReconstruction represents the base surface reconstruction class. More...
class  SurfelSmoothing
class  RegistrationVisualizer
 RegistrationVisualizer represents the base class for rendering the intermediate positions ocupied 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 std::vector
< PointCorrespondence3D,
Eigen::aligned_allocator
< PointCorrespondence3D > > 
PointCorrespondences3DVector
typedef std::vector
< PointCorrespondence6D,
Eigen::aligned_allocator
< PointCorrespondence6D > > 
PointCorrespondences6DVector
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
Correspondences
typedef boost::shared_ptr
< std::vector
< pcl::Correspondence > > 
CorrespondencesPtr
typedef boost::shared_ptr
< const std::vector
< pcl::Correspondence > > 
CorrespondencesConstPtr
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 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 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.
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

Enumerations

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.

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enum  TreeTypes { KDTREE_FLANN, KDTREE_ORGANIZED_INDEX }
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_REGISTRATION, SACMODEL_PARALLEL_PLANE, SACMODEL_NORMAL_PARALLEL_PLANE, SACMODEL_STICK
}

Functions

template<typename PointT >
pcl::PointCloud
< pcl::VFHSignature308 >::Ptr 
computeVFH (typename PointCloud< PointT >::ConstPtr cloud, double radius)
 Helper function to extract the VFH feature describing the given point cloud.
float rad2deg (float alpha)
 Convert an angle from radians to degrees.
float deg2rad (float alpha)
 Convert an angle from degrees to radians.
double rad2deg (double alpha)
 Convert an angle from radians to degrees.
double deg2rad (double alpha)
 Convert an angle from degrees to radians.
template<typename real >
real normAngle (real alpha)
 Normalize an angle to (-PI, PI].
template<typename real >
std::ostream & operator<< (std::ostream &os, const BivariatePolynomialT< real > &p)
template<typename PointT >
void compute3DCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::Vector4f &centroid)
 Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.
template<typename PointT >
void compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Vector4f &centroid)
 Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector.
template<typename PointT >
void compute3DCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Vector4f &centroid)
 Compute the 3D (X-Y-Z) centroid of a set of points using their indices and return it as a 3D vector.
template<typename PointT >
void computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 Compute the 3x3 covariance matrix of a given set of points.
template<typename PointT >
void computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 Compute normalized the 3x3 covariance matrix of a given set of points.
template<typename PointT >
void computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 Compute the 3x3 covariance matrix of a given set of points using their indices.
template<typename PointT >
void computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 Compute the 3x3 covariance matrix of a given set of points using their indices.
template<typename PointT >
void computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 Compute the normalized 3x3 covariance matrix of a given set of points using their indices.
template<typename PointT >
void computeCovarianceMatrixNormalized (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, const Eigen::Vector4f &centroid, Eigen::Matrix3f &covariance_matrix)
 Compute the normalized 3x3 covariance matrix of a given set of points using their indices.
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Vector4f &centroid, pcl::PointCloud< PointT > &cloud_out)
 Subtract a centroid from a point cloud and return the de-meaned representation.
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)
 Subtract a centroid from a point cloud and return the de-meaned representation.
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const Eigen::Vector4f &centroid, Eigen::MatrixXf &cloud_out)
 Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix.
template<typename PointT >
void demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const std::vector< int > &indices, const Eigen::Vector4f &centroid, Eigen::MatrixXf &cloud_out)
 Subtract a centroid from a point cloud and return the de-meaned representation as an Eigen matrix.
template<typename PointT >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, Eigen::VectorXf &centroid)
 General, all purpose nD centroid estimation for a set of points using their indices.
template<typename PointT >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::VectorXf &centroid)
 General, all purpose nD centroid estimation for a set of points using their indices.
template<typename PointT >
void computeNDCentroid (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::VectorXf &centroid)
 General, all purpose nD centroid estimation for a set of points using their indices.
double getAngle3D (const Eigen::Vector4f &v1, const Eigen::Vector4f &v2)
 Compute the smallest angle between two vectors in the [ 0, PI ) interval in 3D.
void getMeanStd (const std::vector< float > &values, double &mean, double &stddev)
 Compute both the mean and the standard deviation of an array of values.
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.
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.
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.
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.
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.
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.
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.
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.
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.
PCL_EXPORTS void getMinMax (const sensor_msgs::PointCloud2 &cloud, int idx, const std::string &field_name, float &min_p, float &max_p)
 Get the minimum and maximum values on a point histogram.
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.
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.
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).
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).
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.
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.
template<typename Scalar , typename Roots >
void computeRoots2 (const Scalar &b, const Scalar &c, Roots &roots)
template<typename Matrix , typename Roots >
void computeRoots (const Matrix &m, Roots &roots)
template<typename Matrix , typename Vector >
void eigen33 (const Matrix &mat, Matrix &evecs, Vector &evals)
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).
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).
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).
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).
void getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis, Eigen::Affine3f &transformation)
 Same as getTransFromUnitVectorsZY - for downwards compatibility.
Eigen::Affine3f getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis)
 Same as getTransFromUnitVectorsZY - for downwards compatibility.
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).
void getEulerAngles (const Eigen::Affine3f &t, float &roll, float &pitch, float &yaw)
 Extract the Euler angles (XYZ-convention) from the given transformation.
void getTranslationAndEulerAngles (const Eigen::Affine3f &t, float &x, float &y, float &z, float &roll, float &pitch, float &yaw)
 Extract x,y,z and the Euler angles (XYZ-convention) from the given transformation.
void getTransformation (float x, float y, float z, float roll, float pitch, float yaw, Eigen::Affine3f &t)
 Create a transformation from the given translation and Euler angles (XYZ-convention).
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).
template<typename Derived >
void saveBinary (const Eigen::MatrixBase< Derived > &matrix, std::ostream &file)
 Write a matrix to an output stream.
template<typename Derived >
void loadBinary (Eigen::MatrixBase< Derived > &matrix, std::istream &file)
 Read a matrix from an input stream.
void getAllPcdFilesInDirectory (const std::string &directory, std::vector< std::string > &file_names)
 Find all *.pcd files in the directory and return them sorted.
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 '/').
std::string getFilenameWithoutExtension (const std::string &input)
 Remove the extension from the given string and return only the filename (everything before the last '.
std::string getFileExtension (const std::string &input)
 Get the file extension from the given string (the remaining string after the last '.
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.
template<typename FloatVectorT >
float L1_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the L1 norm of the vector between two points.
template<typename FloatVectorT >
float L2_Norm_SQR (FloatVectorT A, FloatVectorT B, int dim)
 Compute the squared L2 norm of the vector between two points.
template<typename FloatVectorT >
float L2_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the L2 norm of the vector between two points.
template<typename FloatVectorT >
float Linf_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the L-infinity norm of the vector between two points.
template<typename FloatVectorT >
float JM_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the JM norm of the vector between two points.
template<typename FloatVectorT >
float B_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the B norm of the vector between two points.
template<typename FloatVectorT >
float Sublinear_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the sublinear norm of the vector between two points.
template<typename FloatVectorT >
float CS_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the CS norm of the vector between two points.
template<typename FloatVectorT >
float Div_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the div norm of the vector between two points.
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.
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.
template<typename FloatVectorT >
float KL_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the KL between two discrete probability density functions.
template<typename FloatVectorT >
float HIK_Norm (FloatVectorT A, FloatVectorT B, int dim)
 Compute the HIK norm of the vector between two points.
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.
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.
int getFieldIndex (const sensor_msgs::PointCloud2 &cloud, const std::string &field_name)
 Get the index of a specified field (i.e., dimension/channel).
template<typename PointT >
int getFieldIndex (const pcl::PointCloud< PointT > &cloud, const std::string &field_name, std::vector< sensor_msgs::PointField > &fields)
 Get the index of a specified field (i.e., dimension/channel).
template<typename PointT >
void getFields (const pcl::PointCloud< PointT > &cloud, std::vector< sensor_msgs::PointField > &fields)
 Get the list of available fields (i.e., dimension/channel).
template<typename PointT >
std::string getFieldsList (const pcl::PointCloud< PointT > &cloud)
 Get the list of all fields available in a given cloud.
std::string getFieldsList (const sensor_msgs::PointCloud2 &cloud)
 Get the available point cloud fields as a space separated string.
int getFieldSize (const int datatype)
 Obtains the size of a specific field data type in bytes.
PCL_EXPORTS void getFieldsSizes (const std::vector< sensor_msgs::PointField > &fields, std::vector< int > &field_sizes)
 Obtain a vector with the sizes of all valid fields (e.g., not "_").
int getFieldType (const int size, char type)
 Obtains the type of the PointField from a specific size and type.
char getFieldType (const int type)
 Obtains the type of the PointField from a specific PointField as a char.
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.
PCL_EXPORTS bool concatenatePointCloud (const sensor_msgs::PointCloud2 &cloud1, const sensor_msgs::PointCloud2 &cloud2, sensor_msgs::PointCloud2 &cloud_out)
 Concatenate two sensor_msgs::PointCloud2.
PCL_EXPORTS void copyPointCloud (const sensor_msgs::PointCloud2 &cloud_in, const std::vector< int > &indices, sensor_msgs::PointCloud2 &cloud_out)
 Extract the indices of a given point cloud as a new point cloud.
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.
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.
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.
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.
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.
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.
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.
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.
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.
PCL_EXPORTS bool concatenateFields (const sensor_msgs::PointCloud2 &cloud1_in, const sensor_msgs::PointCloud2 &cloud2_in, sensor_msgs::PointCloud2 &cloud_out)
 Concatenate two datasets representing different fields.
PCL_EXPORTS bool getPointCloudAsEigen (const sensor_msgs::PointCloud2 &in, Eigen::MatrixXf &out)
 Copy the XYZ dimensions of a sensor_msgs::PointCloud2 into Eigen format.
PCL_EXPORTS bool getEigenAsPointCloud (Eigen::MatrixXf &in, sensor_msgs::PointCloud2 &out)
 Copy the XYZ dimensions from an Eigen MatrixXf into a sensor_msgs::PointCloud2 message.
bool isBetterCorrespondence (const PointCorrespondence &pc1, const PointCorrespondence &pc2)
 Comparator to enable us to sort a vector of PointCorrespondences according to their scores using std::sort(begin(), end(), isBetterCorrespondence);.
template<typename PointSource , typename PointTarget >
void estimateRigidTransformationSVD (const pcl::PointCloud< PointSource > &cloud_src, const pcl::PointCloud< PointTarget > &cloud_tgt, Eigen::Matrix4f &transformation_matrix)
 Estimate a rigid rotation transformation between a source and a target point cloud using SVD.
template<typename PointSource , typename PointTarget >
void estimateRigidTransformationSVD (const pcl::PointCloud< PointSource > &cloud_src, const std::vector< int > &indices_src, const pcl::PointCloud< PointTarget > &cloud_tgt, Eigen::Matrix4f &transformation_matrix)
 Estimate a rigid rotation transformation between a source and a target point cloud using SVDlosed-form solution of absolute orientation using unit quaternions.
template<typename PointSource , typename PointTarget >
void estimateRigidTransformationSVD (const pcl::PointCloud< PointSource > &cloud_src, const std::vector< int > &indices_src, const pcl::PointCloud< PointTarget > &cloud_tgt, const std::vector< int > &indices_tgt, Eigen::Matrix4f &transformation_matrix)
 Estimate a rigid rotation transformation between a source and a target point cloud using SVD.
double getTime ()
template<typename PointT >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform)
 Apply an affine transform defined by an Eigen Transform.
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)
 Apply an affine transform defined by an Eigen Transform.
template<typename PointT >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Affine3f &transform)
 Transform a point cloud and rotate its normals using an Eigen transform.
template<typename PointT >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform)
 Apply an affine transform defined by an Eigen Transform.
template<typename PointT >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Matrix4f &transform)
 Transform a point cloud and rotate its normals using an Eigen transform.
template<typename PointT >
void transformPointCloud (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Vector3f &offset, const Eigen::Quaternionf &rotation)
 Apply a rigid transform defined by a 3D offset and a quaternion.
template<typename PointT >
void transformPointCloudWithNormals (const pcl::PointCloud< PointT > &cloud_in, pcl::PointCloud< PointT > &cloud_out, const Eigen::Vector3f &offset, const Eigen::Quaternionf &rotation)
 Transform a point cloud and rotate its normals using an Eigen transform.
template<typename PointT >
PointT transformPoint (const PointT &point, const Eigen::Affine3f &transform)
 Transform a point with members x,y,z.
std::ostream & operator<< (std::ostream &os, const Correspondence &c)
 overloaded << operator
std::ostream & operator<< (std::ostream &os, const PointXYZ &p)
std::ostream & operator<< (std::ostream &os, const PointXYZI &p)
std::ostream & operator<< (std::ostream &os, const PointXYZRGBA &p)
std::ostream & operator<< (std::ostream &os, const PointXYZRGB &p)
std::ostream & operator<< (std::ostream &os, const PointXY &p)
std::ostream & operator<< (std::ostream &os, const InterestPoint &p)
std::ostream & operator<< (std::ostream &os, const Normal &p)
std::ostream & operator<< (std::ostream &os, const PointNormal &p)
std::ostream & operator<< (std::ostream &os, const PointXYZRGBNormal &p)
std::ostream & operator<< (std::ostream &os, const PointXYZINormal &p)
std::ostream & operator<< (std::ostream &os, const PointWithRange &p)
std::ostream & operator<< (std::ostream &os, const PointWithViewpoint &p)
std::ostream & operator<< (std::ostream &os, const MomentInvariants &p)
std::ostream & operator<< (std::ostream &os, const PrincipalRadiiRSD &p)
std::ostream & operator<< (std::ostream &os, const Boundary &p)
std::ostream & operator<< (std::ostream &os, const PrincipalCurvatures &p)
std::ostream & operator<< (std::ostream &os, const PFHSignature125 &p)
std::ostream & operator<< (std::ostream &os, const PPFSignature &p)
std::ostream & operator<< (std::ostream &os, const NormalBasedSignature12 &p)
std::ostream & operator<< (std::ostream &os, const SHOT &p)
std::ostream & operator<< (std::ostream &os, const FPFHSignature33 &p)
std::ostream & operator<< (std::ostream &os, const VFHSignature308 &p)
std::ostream & operator<< (std::ostream &os, const Narf36 &p)
std::ostream & operator<< (std::ostream &os, const BorderDescription &p)
std::ostream & operator<< (std::ostream &os, const IntensityGradient &p)
template<int N>
std::ostream & operator<< (std::ostream &os, const Histogram< N > &p)
std::ostream & operator<< (std::ostream &os, const PointWithScale &p)
std::ostream & operator<< (std::ostream &os, const PointSurfel &p)
template<typename PointType1 , typename PointType2 >
float squaredEuclideanDistance (const PointType1 &p1, const PointType2 &p2)
 Calculate the squared euclidean distance between the two given points.
template<typename PointType1 , typename PointType2 >
float euclideanDistance (const PointType1 &p1, const PointType2 &p2)
 Calculate the euclidean distance between the two given points.
template<typename PointType >
bool hasValidXYZ (const PointType &p)
 Checks if x,y,z are finite numbers.
std::ostream & operator<< (std::ostream &s, const ::pcl::ModelCoefficients &v)
template<typename PointT >
std::ostream & operator<< (std::ostream &s, const pcl::PointCloud< PointT > &p)
std::ostream & operator<< (std::ostream &s, const ::pcl::PointIndices &v)
std::ostream & operator<< (std::ostream &s, const ::pcl::PolygonMesh &v)
template<typename PointT >
void createMapping (const std::vector< sensor_msgs::PointField > &msg_fields, MsgFieldMap &field_map)
template<typename PointT >
void fromROSMsg (const sensor_msgs::PointCloud2 &msg, pcl::PointCloud< PointT > &cloud, const MsgFieldMap &field_map)
template<typename PointT >
void fromROSMsg (const sensor_msgs::PointCloud2 &msg, pcl::PointCloud< PointT > &cloud)
template<typename PointT >
void toROSMsg (const pcl::PointCloud< PointT > &cloud, sensor_msgs::PointCloud2 &msg)
template<typename CloudT >
void toROSMsg (const CloudT &cloud, sensor_msgs::Image &msg)
 Copy the RGB fields of a PointCloud into sensor_msgs::Image format.
void toROSMsg (const sensor_msgs::PointCloud2 &cloud, sensor_msgs::Image &msg)
 Copy the RGB fields of a PointCloud2 msg into sensor_msgs::Image format.
template<typename Sequence , typename F >
void for_each_type (F f)
std::ostream & operator<< (std::ostream &s, const ::pcl::Vertices &v)
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.
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.
std::ostream & operator<< (std::ostream &os, const RangeImageBorderExtractor::Parameters &p)
template<typename PointT >
void 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.
template<typename PointT >
void 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.
template<typename PointT >
void flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Vector4f &normal)
 Flip (in place) the estimated normal of a point towards a given viewpoint.
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.
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.
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<typename PointInT , typename PointNT , typename PointOutT >
void computeRSD (const pcl::PointCloud< PointInT > &surface, const pcl::PointCloud< PointNT > &normals, const std::vector< int > &indices, double max_dist, int nr_subdiv, double plane_radius, PointOutT &radii)
 Estimate the Radius-based Surface Descriptor (RSD) for a given point based on its spatial neighborhood of 3D points with normals.
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.
PCL_EXPORTS void getMinMax3D (const sensor_msgs::PointCloud2ConstPtr &cloud, int x_idx, int y_idx, int z_idx, Eigen::Vector4f &min_pt, Eigen::Vector4f &max_pt)
PCL_EXPORTS void getMinMax3D (const sensor_msgs::PointCloud2ConstPtr &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)
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.
template<typename T >
pcl_atoa (const char *nptr)
 templated atoi() / atof() wrapper
template<>
char pcl_atoa< char > (const char *nptr)
template<>
unsigned char pcl_atoa< unsigned char > (const char *nptr)
template<>
signed char pcl_atoa< signed char > (const char *nptr)
template<>
short int pcl_atoa< short int > (const char *nptr)
template<>
short unsigned int pcl_atoa< short unsigned int > (const char *nptr)
template<>
int pcl_atoa< int > (const char *nptr)
template<>
unsigned int pcl_atoa< unsigned int > (const char *nptr)
template<>
float pcl_atoa< float > (const char *nptr)
template<>
double pcl_atoa< double > (const char *nptr)
template<typename Type >
void copyValueString (const sensor_msgs::PointCloud2 &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.
template<>
void copyValueString< int8_t > (const sensor_msgs::PointCloud2 &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 sensor_msgs::PointCloud2 &cloud, const unsigned int point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count, std::ostream &stream)
void throwPCLIOException (const char *function, const char *file, unsigned line, const char *format,...)
 /brief /ingroup io
template<typename PointT >
void initTree (const int &spatial_locator, boost::shared_ptr< pcl::KdTree< PointT > > &tree, int k=0)
 Initialize the spatial locator used for nearest neighbor search.
std::ostream & operator<< (std::ostream &os, const NarfKeypoint::Parameters &p)
std::ostream & operator<< (std::ostream &os, const RangeImage &r)
 /ingroup range_image
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.
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.
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.
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.
template<typename PointT >
void extractEuclideanClusters (const PointCloud< PointT > &cloud, const boost::shared_ptr< KdTree< 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.
template<typename PointT >
void extractEuclideanClusters (const PointCloud< PointT > &cloud, const std::vector< int > &indices, const boost::shared_ptr< KdTree< 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.
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.
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.
bool comparePointClusters (const pcl::PointIndices &a, const pcl::PointIndices &b)
 Sort clusters method (for std::sort).
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.
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.
template<typename PointT >
void getPointCloudDifference (const pcl::PointCloud< PointT > &src, const pcl::PointCloud< PointT > &tgt, double threshold, const boost::shared_ptr< pcl::KdTree< PointT > > &tree, pcl::PointCloud< PointT > &output)
 Obtain the difference between two aligned point clouds as another point cloud, given a distance threshold.
bool comparePoints2D (const std::pair< int, Eigen::Vector4f > &p1, const std::pair< int, Eigen::Vector4f > &p2)
 Sort 2D points in a vector structure.
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.

Variables

const int I_SHIFT_EP [12][2]
 The 12 edges of a cell.
const int I_SHIFT_PT [4]
const int I_SHIFT_EDGE [3][2]
const unsigned int edgeTable [256]
const int triTable [256][16]

Detailed Description

Software License Agreement (BSD License).

Copyright (c) 2011, Willow Garage, Inc. All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

* Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of Willow Garage, Inc. nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Author: Suat Gedikli (gedikli@willowgarage.com)


Typedef Documentation

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

Definition at line 136 of file point_types.hpp.

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

Definition at line 137 of file point_types.hpp.

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

Definition at line 138 of file point_types.hpp.

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

Definition at line 139 of file point_types.hpp.

Definition at line 99 of file bivariate_polynomial.h.

Definition at line 98 of file bivariate_polynomial.h.

Definition at line 84 of file correspondence.h.

typedef boost::shared_ptr<const std::vector<pcl::Correspondence> > pcl::CorrespondencesConstPtr

Definition at line 86 of file correspondence.h.

typedef boost::shared_ptr<std::vector<pcl::Correspondence> > pcl::CorrespondencesPtr

Definition at line 85 of file correspondence.h.

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

Definition at line 64 of file pcl_base.h.

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

Definition at line 63 of file pcl_base.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 64 of file point_cloud.h.

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

Definition at line 75 of file point_correspondence.h.

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

Definition at line 90 of file point_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 123 of file polynomial_calculations.h.

Definition at line 122 of file polynomial_calculations.h.

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

Definition at line 96 of file TextureMesh.h.

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

Definition at line 95 of file TextureMesh.h.

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

Definition at line 140 of file point_types.hpp.

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

Definition at line 141 of file point_types.hpp.

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

Definition at line 142 of file point_types.hpp.

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

Definition at line 143 of file point_types.hpp.

Definition at line 110 of file vector_average.h.

Definition at line 111 of file vector_average.h.

Definition at line 112 of file vector_average.h.

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

Definition at line 26 of file Vertices.h.

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

Definition at line 25 of file Vertices.h.


Enumeration Type Documentation

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_REGISTRATION 
SACMODEL_PARALLEL_PLANE 
SACMODEL_NORMAL_PARALLEL_PLANE 
SACMODEL_STICK 

Definition at line 45 of file model_types.h.

Enumerator:
KDTREE_FLANN 
KDTREE_ORGANIZED_INDEX 

Definition at line 45 of file tree_types.h.


Function Documentation

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 
)
template<typename Matrix , typename Roots >
void pcl::computeRoots ( const Matrix &  m,
Roots &  roots 
) [inline]

Definition at line 115 of file eigen.h.

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

Definition at line 101 of file eigen.h.

template<typename PointT >
pcl::PointCloud<pcl::VFHSignature308>::Ptr pcl::computeVFH ( typename PointCloud< PointT >::ConstPtr  cloud,
double  radius 
)

Helper function to extract the VFH feature describing the given point cloud.

Parameters:
points point cloud for feature extraction
radius search radius for normal estimation
Returns:
point cloud containing the extracted feature

Definition at line 57 of file vfh_nn_classifier.h.

template<typename Type >
void pcl::copyValueString ( const sensor_msgs::PointCloud2 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] cloud the cloud to copy from
[in] point_index the index of the point
[in] point_size the size of the point in the cloud
[in] field_idx the index of the dimension/field
[in] fields_count the current fields count
[out] stream the ostringstream to copy into

Definition at line 304 of file file_io.h.

template<>
void pcl::copyValueString< int8_t > ( const sensor_msgs::PointCloud2 cloud,
const unsigned int  point_index,
const int  point_size,
const unsigned int  field_idx,
const unsigned int  fields_count,
std::ostream &  stream 
) [inline]
template<>
void pcl::copyValueString< uint8_t > ( const sensor_msgs::PointCloud2 cloud,
const unsigned int  point_index,
const int  point_size,
const unsigned int  field_idx,
const unsigned int  fields_count,
std::ostream &  stream 
) [inline]
template<typename PointT >
void pcl::createMapping ( const std::vector< sensor_msgs::PointField > &  msg_fields,
MsgFieldMap &  field_map 
)

Todo:
One could construct a pathological case where the struct has a field where the serialized data has padding

Definition at line 123 of file conversions.h.

template<typename Matrix , typename Vector >
void pcl::eigen33 ( const Matrix &  mat,
Matrix &  evecs,
Vector &  evals 
)

Definition at line 180 of file eigen.h.

template<typename PointType1 , typename PointType2 >
float pcl::euclideanDistance ( const PointType1 &  p1,
const PointType2 &  p2 
) [inline]

Calculate the euclidean distance between the two given points.

template<typename Sequence , typename F >
void pcl::for_each_type ( f  )  [inline]

Definition at line 85 of file for_each_type.h.

template<typename PointT >
void pcl::fromROSMsg ( const sensor_msgs::PointCloud2 msg,
pcl::PointCloud< PointT > &  cloud,
const MsgFieldMap &  field_map 
)

Definition at line 154 of file conversions.h.

template<typename PointT >
void pcl::fromROSMsg ( const sensor_msgs::PointCloud2 msg,
pcl::PointCloud< PointT > &  cloud 
)

Definition at line 208 of file conversions.h.

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:
directory the directory to be searched
file_names the resulting (sorted) list of .pcd files

Definition at line 40 of file file_io.hpp.

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

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

Parameters:
[in] fields the input vector containing the fields
[out] field_sizes the resultant field sizes in bytes
std::string pcl::getFileExtension ( const std::string &  input  )  [inline]

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

')

Parameters:
input the input filename
Returns:
input 's file extension

Definition at line 75 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:
input the input filename (with the file extension)
Returns:
the resulting filename, stripped of its extension

Definition at line 69 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:
input the input filename (with full path)
Returns:
the resulting filename, stripped of the path

Definition at line 63 of file file_io.hpp.

template<typename PointT >
void pcl::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.

Parameters:
cloud the point cloud data message
distance_field_name the field name that contains the distance values
min_distance the minimum distance a point will be considered from
max_distance the maximum distance a point will be considered to
min_pt the resultant minimum bounds
max_pt the resultant maximum bounds
limit_negative if set to true, then all points outside of the interval (min_distance;max_distace) are considered

Definition at line 45 of file voxel_grid.hpp.

PCL_EXPORTS void pcl::getMinMax3D ( const sensor_msgs::PointCloud2ConstPtr cloud,
int  x_idx,
int  y_idx,
int  z_idx,
Eigen::Vector4f &  min_pt,
Eigen::Vector4f &  max_pt 
)
PCL_EXPORTS void pcl::getMinMax3D ( const sensor_msgs::PointCloud2ConstPtr 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 
)
double pcl::getTime (  )  [inline]

Definition at line 84 of file time.h.

Eigen::Affine3f pcl::getTransformationFromTwoUnitVectors ( const Eigen::Vector3f &  y_direction,
const Eigen::Vector3f &  z_axis 
) [inline]

Same as getTransFromUnitVectorsZY - for downwards compatibility.

Definition at line 82 of file eigen.hpp.

void pcl::getTransformationFromTwoUnitVectors ( const Eigen::Vector3f &  y_direction,
const Eigen::Vector3f &  z_axis,
Eigen::Affine3f &  transformation 
) [inline]

Same as getTransFromUnitVectorsZY - for downwards compatibility.

Definition at line 77 of file eigen.hpp.

template<typename PointType >
bool pcl::hasValidXYZ ( const PointType &  p  )  [inline]

Checks if x,y,z are finite numbers.

std::ostream& pcl::operator<< ( std::ostream &  os,
const MomentInvariants &  p 
) [inline]

Definition at line 590 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const InterestPoint &  p 
) [inline]

Definition at line 382 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const NormalBasedSignature12 &  p 
) [inline]

Definition at line 682 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointXYZRGB &  p 
) [inline]

Definition at line 346 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointXY &  p 
) [inline]

Definition at line 360 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const FPFHSignature33 &  p 
) [inline]

Definition at line 768 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const Narf36 &  p 
) [inline]

Definition at line 797 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointNormal &  p 
) [inline]

Definition at line 427 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const IntensityGradient &  p 
) [inline]

Definition at line 837 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointWithScale &  p 
) [inline]

Definition at line 868 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const Boundary &  p 
) [inline]

Definition at line 616 of file point_types.hpp.

template<int N>
std::ostream& pcl::operator<< ( std::ostream &  os,
const Histogram< N > &  p 
) [inline]

Definition at line 852 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointXYZI &  p 
) [inline]

Definition at line 229 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  s,
const ::pcl::ModelCoefficients v 
) [inline]

Definition at line 30 of file ModelCoefficients.h.

std::ostream& pcl::operator<< ( std::ostream &  os,
const Correspondence &  c 
) [inline]

overloaded << operator

Definition at line 78 of file correspondence.h.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PFHSignature125 &  p 
) [inline]

Definition at line 653 of file point_types.hpp.

template<typename PointT >
std::ostream& pcl::operator<< ( std::ostream &  s,
const pcl::PointCloud< PointT > &  p 
)

Definition at line 334 of file point_cloud.h.

std::ostream& pcl::operator<< ( std::ostream &  os,
const RangeImageBorderExtractor::Parameters &  p 
) [inline]

Definition at line 57 of file range_image_border_extractor.hpp.

std::ostream& pcl::operator<< ( std::ostream &  s,
const ::pcl::PolygonMesh v 
) [inline]

Definition at line 35 of file PolygonMesh.h.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointXYZ &  p 
) [inline]

Definition at line 173 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  s,
const ::pcl::Vertices v 
) [inline]

Definition at line 28 of file Vertices.h.

std::ostream& pcl::operator<< ( std::ostream &  os,
const VFHSignature308 &  p 
) [inline]

Definition at line 782 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PrincipalCurvatures &  p 
) [inline]

Definition at line 640 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const SHOT &  p 
) [inline]

Definition at line 698 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PPFSignature &  p 
) [inline]

Definition at line 668 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointXYZRGBA &  p 
) [inline]

Definition at line 272 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointWithViewpoint &  p 
) [inline]

Definition at line 577 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointSurfel &  p 
) [inline]

Definition at line 894 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointXYZINormal &  p 
) [inline]

Definition at line 522 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const Normal &  p 
) [inline]

Definition at line 404 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const RangeImage &  r 
) [inline]

/ingroup range_image

Definition at line 691 of file range_image.h.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointWithRange &  p 
) [inline]

Definition at line 544 of file point_types.hpp.

template<typename real >
std::ostream & pcl::operator<< ( std::ostream &  os,
const BivariatePolynomialT< real > &  p 
)

Definition at line 192 of file bivariate_polynomial.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PrincipalRadiiRSD &  p 
) [inline]

Definition at line 603 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  s,
const ::pcl::PointIndices v 
) [inline]

Definition at line 29 of file PointIndices.h.

std::ostream& pcl::operator<< ( std::ostream &  os,
const BorderDescription &  p 
) [inline]

Definition at line 815 of file point_types.hpp.

std::ostream& pcl::operator<< ( std::ostream &  os,
const PointXYZRGBNormal &  p 
) [inline]

Definition at line 498 of file point_types.hpp.

template<typename T >
T pcl::pcl_atoa ( const char *  nptr  )  [inline]

templated atoi() / atof() wrapper

Parameters:
nptr the string to convert

Definition at line 53 of file file_io.h.

template<>
char pcl::pcl_atoa< char > ( const char *  nptr  )  [inline]
template<>
double pcl::pcl_atoa< double > ( const char *  nptr  )  [inline]
template<>
float pcl::pcl_atoa< float > ( const char *  nptr  )  [inline]
template<>
int pcl::pcl_atoa< int > ( const char *  nptr  )  [inline]
template<>
short int pcl::pcl_atoa< short int > ( const char *  nptr  )  [inline]
template<>
short unsigned int pcl::pcl_atoa< short unsigned int > ( const char *  nptr  )  [inline]
template<>
signed char pcl::pcl_atoa< signed char > ( const char *  nptr  )  [inline]
template<>
unsigned char pcl::pcl_atoa< unsigned char > ( const char *  nptr  )  [inline]
template<>
unsigned int pcl::pcl_atoa< unsigned int > ( const char *  nptr  )  [inline]
template<typename PointType1 , typename PointType2 >
float pcl::squaredEuclideanDistance ( const PointType1 &  p1,
const PointType2 &  p2 
) [inline]

Calculate the squared euclidean distance between the two given points.

void pcl::throwPCLIOException ( const char *  function,
const char *  file,
unsigned  line,
const char *  format,
  ... 
) [inline]

/brief /ingroup io

Definition at line 67 of file pcl_io_exception.h.

void pcl::toROSMsg ( const sensor_msgs::PointCloud2 cloud,
sensor_msgs::Image msg 
) [inline]

Copy the RGB fields of a PointCloud2 msg into sensor_msgs::Image format.

Parameters:
cloud the point cloud message
msg the resultant sensor_msgs::Image will throw std::runtime_error if there is a problem

Definition at line 288 of file conversions.h.

template<typename PointT >
void pcl::toROSMsg ( const pcl::PointCloud< PointT > &  cloud,
sensor_msgs::PointCloud2 msg 
)

Todo:
msg.is_bigendian = ?;

Definition at line 216 of file conversions.h.

template<typename CloudT >
void pcl::toROSMsg ( const CloudT &  cloud,
sensor_msgs::Image msg 
)

Copy the RGB fields of a PointCloud into sensor_msgs::Image format.

Parameters:
cloud the point cloud message
msg the resultant sensor_msgs::Image CloudT cloud type, CloudT should be akin to pcl::PointCloud<pcl::PointXYZRGB> will throw std::runtime_error if there is a problem

Definition at line 254 of file conversions.h.

template<typename PointT >
void pcl::transformPointCloudWithNormals ( const pcl::PointCloud< PointT > &  cloud_in,
pcl::PointCloud< PointT > &  cloud_out,
const Eigen::Affine3f &  transform 
)

Transform a point cloud and rotate its normals using an Eigen transform.

Parameters:
cloud_in the input point cloud
cloud_out the resultant output point cloud
transform an affine transformation (typically a rigid transformation)
Note:
The density of the point cloud is lost, since density implies that the origin is the point of view
Can be used with cloud_in equal to cloud_out

Definition at line 117 of file transforms.hpp.


Variable Documentation

const unsigned int pcl::edgeTable[256]

Definition at line 59 of file marching_cubes.h.

const int pcl::I_SHIFT_EDGE[3][2]
Initial value:
 {
    {0,1}, {1,3}, {1,2}
  }

Definition at line 58 of file grid_projection.h.

const int pcl::I_SHIFT_EP[12][2]
Initial value:
 {
    {0, 4}, {1, 5}, {2, 6}, {3, 7}, 
    {0, 1}, {1, 2}, {2, 3}, {3, 0},
    {4, 5}, {5, 6}, {6, 7}, {7, 4}
  }

The 12 edges of a cell.

Definition at line 48 of file grid_projection.h.

const int pcl::I_SHIFT_PT[4]
Initial value:
 {
    0, 4, 5, 7
  }

Definition at line 54 of file grid_projection.h.

const int pcl::triTable[256][16]

Definition at line 93 of file marching_cubes.h.