Point Cloud Library (PCL)
1.6.0

flann  
openni_wrapper  
IRImage  Class containing just a reference to IR meta data 
pcl  
@77  
apps  
DominantPlaneSegmentation  DominantPlaneSegmentation performs euclidean segmentation on a scene assuming that a dominant plane exists 
RenderViewsTesselatedSphere  Class to render synthetic views of a 3D mesh using a tesselated sphere NOTE: This class should replace renderViewTesselatedSphere from pcl::visualization 
common  
IntensityFieldAccessor< pcl::PointNormal >  
IntensityFieldAccessor< pcl::PointXYZRGB >  
IntensityFieldAccessor< pcl::PointXYZRGBA >  
IntensityFieldAccessor  
ComparisonOps  
console  
TicToc  
detail  
FieldMapping  
FieldAdder  
FieldMapper  
distances  
fields  
geometry  
io  
ply  
io_operators  
ply_parser  Class ply_parser parses a PLY file and generates appropriate atomic parsers for the body 
list_property_begin_callback_type  
list_property_definition_callback_type  
list_property_definition_callbacks_type  
list_property_element_callback_type  
list_property_end_callback_type  
scalar_property_callback_type  
scalar_property_definition_callback_type  
scalar_property_definition_callbacks_type  
TARHeader  A TAR file's header, as described on http://en.wikipedia.org/wiki/Tar_%28file_format%29 
octree  
ColorCoding  ColorCoding class 
configurationProfile_t  
PointCloudCompression  Octree pointcloud compression class 
PointCoding  PointCoding class 
BufferedBranchNode  
Octree2BufBase  Octree double buffer class 
OctreeBase  Octree class 
OctreeContainerEmpty  Octree leaf class that does not store any information 
OctreeContainerDataT  Octree leaf class that does store a single DataT element 
OctreeContainerDataTVector  Octree leaf class that does store a vector of DataT elements 
OctreeIteratorBase  Abstract octree iterator class 
OctreeDepthFirstIterator  Octree iterator class 
OctreeBreadthFirstIterator  Octree iterator class 
OctreeLeafNodeIterator  Octree leaf node iterator class 
OctreeKey  Octree key class 
OctreeNodePool  Octree node pool 
OctreeNode  Abstract octree node class 
OctreeLeafNode  Abstract octree leaf class 
OctreeBranchNode  Abstract octree branch class 
OctreePointCloud  Octree pointcloud class 
OctreePointCloudChangeDetector  Octree pointcloud change detector class 
OctreePointCloudDensityContainer  Octree pointcloud density leaf node class 
OctreePointCloudDensity  Octree pointcloud density class 
OctreePointCloudOccupancy  Octree pointcloud occupancy class 
OctreePointCloudPointVector  Octree pointcloud point vector class 
OctreePointCloudSinglePoint  Octree pointcloud single point class 
OctreePointCloudVoxelCentroid  Octree pointcloud voxel centroid class 
OctreePointCloudSearch  Octree pointcloud search class 
prioBranchQueueEntry  Priority queue entry for branch nodes 
prioPointQueueEntry  Priority queue entry for point candidates 
registration  
CorrespondenceEstimation  CorrespondenceEstimation represents the base class for determining correspondences between target and query point sets/features 
CorrespondenceEstimationNormalShooting  CorrespondenceEstimationNormalShooting computes correspondences as points in the target cloud which have minimum distance to normals computed on the input cloud 
CorrespondenceRejector  CorrespondenceRejector represents the base class for correspondence rejection methods 
DataContainerInterface  DataContainerInterface provides a generic interface for computing correspondence scores between correspondent points in the input and target clouds 
DataContainer  DataContainer is a container for the input and target point clouds and implements the interface to compute correspondence scores between correspondent points in the input and target clouds 
CorrespondenceRejectorDistance  CorrespondenceRejectorDistance implements a simple correspondence rejection method based on thresholding the distances between the correspondences 
CorrespondenceRejectorFeatures  CorrespondenceRejectorFeatures implements a correspondence rejection method based on a set of feature descriptors 
FeatureContainer  An inner class containing pointers to the source and target feature clouds and the parameters needed to perform the correspondence search 
FeatureContainerInterface  
CorrespondenceRejectorMedianDistance  CorrespondenceRejectorMedianDistance implements a simple correspondence rejection method based on thresholding based on the median distance between the correspondences 
CorrespondenceRejectorOneToOne  CorrespondenceRejectorOneToOne implements a correspondence rejection method based on eliminating duplicate match indices in the correspondences 
CorrespondenceRejectorSampleConsensus  CorrespondenceRejectorSampleConsensus implements a correspondence rejection using Random Sample Consensus to identify inliers (and reject outliers) 
CorrespondenceRejectorSurfaceNormal  CorrespondenceRejectorSurfaceNormal implements a simple correspondence rejection method based on the angle between the normals at correspondent points 
CorrespondenceRejectorTrimmed  CorrespondenceRejectorTrimmed implements a correspondence rejection for ICPlike registration algorithms that uses only the best 'k' correspondences where 'k' is some estimate of the overlap between the two point clouds being registered 
CorrespondenceRejectorVarTrimmed  CorrespondenceRejectoVarTrimmed implements a simple correspondence rejection method by considering as inliers a certain percentage of correspondences with the least distances 
sortCorrespondencesByQueryIndex  sortCorrespondencesByQueryIndex : a functor for sorting correspondences by query index 
sortCorrespondencesByMatchIndex  sortCorrespondencesByMatchIndex : a functor for sorting correspondences by match index 
sortCorrespondencesByDistance  sortCorrespondencesByDistance : a functor for sorting correspondences by distance 
sortCorrespondencesByQueryIndexAndDistance  sortCorrespondencesByQueryIndexAndDistance : a functor for sorting correspondences by query index and distance 
sortCorrespondencesByMatchIndexAndDistance  sortCorrespondencesByMatchIndexAndDistance : a functor for sorting correspondences by match index and distance 
ELCH  ELCH (Explicit Loop Closing Heuristic) class 
Vertex  
TransformationEstimation  TransformationEstimation represents the base class for methods for transformation estimation based on: 
TransformationEstimationLM  TransformationEstimationLM implements Levenberg Marquardtbased estimation of the transformation aligning the given correspondences 
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 
OptimizationFunctor  
OptimizationFunctorWithIndices  
TransformationEstimationPointToPlane  TransformationEstimationPointToPlane uses Levenberg Marquardt optimization to find the transformation that minimizes the pointtoplane distance between the given correspondences 
TransformationEstimationPointToPlaneLLS  TransformationEstimationPointToPlaneLLS implements a Linear Least Squares (LLS) approximation for minimizing the pointtoplane distance between two clouds of corresponding points with normals 
TransformationEstimationSVD  TransformationEstimationSVD implements SVDbased estimation of the transformation aligning the given correspondences 
TransformationValidation  TransformationValidation represents the base class for methods that validate the correctness of a transformation found through TransformationEstimation 
TransformationValidationEuclidean  TransformationValidationEuclidean computes an L2SQR norm between a source and target dataset 
search  
BruteForce  Implementation of a simple brute force search algorithm 
FlannSearch  search::FlannSearch is a generic FLANN wrapper class for the new search interface 
FlannIndexCreator  Helper class that creates a FLANN index from a given FLANN matrix 
KdTreeIndexCreator  Creates a FLANN KdTreeSingleIndex from the given input data 
KdTree  search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search functions using KdTree structure 
Octree  search::Octree is a wrapper class which implements nearest neighbor search operations based on the pcl::octree::Octree structure 
OrganizedNeighbor  OrganizedNeighbor is a class for optimized nearest neigbhor search in organized point clouds 
Entry  
Search  Generic search class 
surface  
SimplificationRemoveUnusedVertices  
test  Test_macros.h provide helper macros for testing vectors, matrices etc 
texture_mapping  
Camera  Structure to store camera pose and focal length 
UvIndex  Structure that links a uv coordinate to its 3D point and face 
tracking  
ApproxNearestPairPointCloudCoherence  ApproxNearestPairPointCloudCoherence computes coherence between two pointclouds using the approximate nearest point pairs 
PointCoherence  PointCoherence is a base class to compute coherence between the two points 
PointCloudCoherence  PointCloudCoherence is a base class to compute coherence between the two PointClouds 
DistanceCoherence  DistanceCoherence computes coherence between two points from the distance between them 
HSVColorCoherence  HSVColorCoherence computes coherence between the two points from the color difference between them 
RGBValue  
_ParticleXYZRPY  
ParticleXYZRPY  
_ParticleXYZR  
ParticleXYZR  
_ParticleXYRPY  
ParticleXYRPY  
_ParticleXYRP  
ParticleXYRP  
_ParticleXYR  
ParticleXYR  
KLDAdaptiveParticleFilterTracker  KLDAdaptiveParticleFilterTracker tracks the PointCloud which is given by setReferenceCloud within the measured PointCloud using particle filter method 
KLDAdaptiveParticleFilterOMPTracker  KLDAdaptiveParticleFilterOMPTracker tracks the PointCloud which is given by setReferenceCloud within the measured PointCloud using particle filter method 
NearestPairPointCloudCoherence  NearestPairPointCloudCoherence computes coherence between two pointclouds using the nearest point pairs 
NormalCoherence  NormalCoherence computes coherence between two points from the angle between their normals 
ParticleFilterTracker  ParticleFilterTracker tracks the PointCloud which is given by setReferenceCloud within the measured PointCloud using particle filter method 
ParticleFilterOMPTracker  ParticleFilterOMPTracker tracks the PointCloud which is given by setReferenceCloud within the measured PointCloud using particle filter method in parallel, using the OpenMP standard 
Tracker  Tracker represents the base tracker class 
traits  
asEnum  
asEnum< int8_t >  
asEnum< uint8_t >  
asEnum< int16_t >  
asEnum< uint16_t >  
asEnum< int32_t >  
asEnum< uint32_t >  
asEnum< float >  
asEnum< double >  
asType  
asType< sensor_msgs::PointField::INT8 >  
asType< sensor_msgs::PointField::UINT8 >  
asType< sensor_msgs::PointField::INT16 >  
asType< sensor_msgs::PointField::UINT16 >  
asType< sensor_msgs::PointField::INT32 >  
asType< sensor_msgs::PointField::UINT32 >  
asType< sensor_msgs::PointField::FLOAT32 >  
asType< sensor_msgs::PointField::FLOAT64 >  
decomposeArray  
POD  
name  
offset  
datatype  
fieldList  
utils  
visualization  
CloudViewer  Simple point cloud visualization class 
CloudActor  
Camera  Camera class holds a set of camera parameters together with the window pos/size 
FPSCallback  
FloatImageUtils  Provide some gerneral functionalities regarding 2d float arrays, e.g., for visualization purposes 
RenWinInteract  
PCLHistogramVisualizer  PCL histogram visualizer main class 
ImageViewer  ImageViewer is a class for 2D image visualization 
ExitCallback  
ExitMainLoopTimerCallback  
PCLVisualizerInteractor  The PCLVisualizer interactor 
PCLVisualizerInteractorStyle  PCLVisualizerInteractorStyle defines an unique, custom VTK based interactory style for PCL Visualizer applications 
PCLHistogramVisualizerInteractorStyle  PCL histogram visualizer interactory style class 
KeyboardEvent  /brief Class representing key hit/release events 
MouseEvent  
PCLVisualizer  PCL Visualizer main class 
PointCloudGeometryHandler  Base handler class for PointCloud geometry 
PointCloudGeometryHandlerXYZ  XYZ handler class for PointCloud geometry 
PointCloudGeometryHandlerSurfaceNormal  Surface normal handler class for PointCloud geometry 
PointCloudGeometryHandlerCustom  Custom handler class for PointCloud geometry 
PointCloudGeometryHandler< sensor_msgs::PointCloud2 >  Base handler class for PointCloud geometry 
PointCloudGeometryHandlerXYZ< sensor_msgs::PointCloud2 >  XYZ handler class for PointCloud geometry 
PointCloudGeometryHandlerSurfaceNormal< sensor_msgs::PointCloud2 >  Surface normal handler class for PointCloud geometry 
PointCloudGeometryHandlerCustom< sensor_msgs::PointCloud2 >  Custom handler class for PointCloud geometry 
PointCloudColorHandler  Base Handler class for PointCloud colors 
PointCloudColorHandlerRandom  Handler for random PointCloud colors (i.e., R, G, B will be randomly chosen) 
PointCloudColorHandlerCustom  Handler for predefined user colors 
PointCloudColorHandlerRGBField  RGB handler class for colors 
PointCloudColorHandlerHSVField  HSV handler class for colors 
PointCloudColorHandlerGenericField  Generic field handler class for colors 
PointCloudColorHandler< sensor_msgs::PointCloud2 >  Base Handler class for PointCloud colors 
PointCloudColorHandlerRandom< sensor_msgs::PointCloud2 >  Handler for random PointCloud colors (i.e., R, G, B will be randomly chosen) 
PointCloudColorHandlerCustom< sensor_msgs::PointCloud2 >  Handler for predefined user colors 
PointCloudColorHandlerRGBField< sensor_msgs::PointCloud2 >  RGB handler class for colors 
PointCloudColorHandlerHSVField< sensor_msgs::PointCloud2 >  HSV handler class for colors 
PointCloudColorHandlerGenericField< sensor_msgs::PointCloud2 >  Generic field handler class for colors 
PointPickingCallback  
PointPickingEvent  /brief Class representing 3D point picking events 
RangeImageVisualizer  Range image visualizer class 
PCLImageCanvasSource2D  PclImageCanvasSource2D represents our own custom version of vtkImageCanvasSource2D, used by the ImageViewer class 
Window  
ExitCallback  
ExitMainLoopTimerCallback  
NNClassification  Nearest neighbor search based classification of PCL point type features 
VFHClassifierNN  Utility class for nearest neighbor search based classification of VFH features 
ChannelProperties  ChannelProperties stores the properties of each channel in a cloud, namely: 
CloudProperties  CloudProperties stores a list of optional point cloud properties such as: 
BivariatePolynomialT  This represents a bivariate polynomial and provides some functionality for it 
NdCentroidFunctor  Helper functor structure for nD centroid estimation 
NdConcatenateFunctor  Helper functor structure for concatenate 
GaussianKernel  Class GaussianKernel assembles all the method for computing, convolving, smoothing, gradients computing an image using a gaussian kernel 
PCA  Principal Component analysis (PCA) class 
PiecewiseLinearFunction  This provides functionalities to efficiently return values for piecewise linear function 
PolynomialCalculationsT  This provides some functionality for polynomials, like finding roots or approximating bivariate polynomials 
Parameters  Parameters used in this class 
PosesFromMatches  Calculate 3D transformation based on point correspondencdes 
Parameters  Parameters used in this class 
PoseEstimate  A result of the pose estimation process 
IsBetter  
Synchronizer  /brief This template class synchronizes two data streams of different types 
StopWatch  Simple stopwatch 
ScopeTime  Class to measure the time spent in a scope 
TimeTrigger  Timer class that invokes registered callback methods periodically 
TransformationFromCorrespondences  Calculates a transformation based on corresponding 3D points 
VectorAverage  Calculates the weighted average and the covariance matrix 
Correspondence  Correspondence represents a match between two entities (e.g., points, descriptors, etc) 
PointCorrespondence3D  Representation of a (possible) correspondence between two 3D points in two different coordinate frames (e.g 
PointCorrespondence6D  Representation of a (possible) correspondence between two points (e.g 
PCLException  A base class for all pcl exceptions which inherits from std::runtime_error 
InvalidConversionException  An exception that is thrown when a PointCloud2 message cannot be converted into a PCL type 
IsNotDenseException  An exception that is thrown when a PointCloud is not dense but is attemped to be used as dense 
InvalidSACModelTypeException  An exception that is thrown when a sample consensus model doesn't have the correct number of samples defined in model_types.h 
IOException  An exception that is thrown during an IO error (typical read/write errors) 
InitFailedException  An exception thrown when init can not be performed should be used in all the PCLBase class inheritants 
UnorganizedPointCloudException  An exception that is thrown when an organized point cloud is needed but not provided 
KernelWidthTooSmallException  An exception that is thrown when the kernel size is too small 
UnhandledPointTypeException  
ComputeFailedException  
for_each_type_impl  
for_each_type_impl< false >  
intersect  
_PointXYZ  
PointXYZ  A point structure representing Euclidean xyz coordinates 
RGB  A structure representing RGB color information 
_PointXYZI  A point structure representing Euclidean xyz coordinates, and the intensity value 
PointXYZI  
_PointXYZL  
PointXYZL  
Label  
_PointXYZRGBA  A point structure representing Euclidean xyz coordinates, and the RGBA color 
PointXYZRGBA  
_PointXYZRGB  
_PointXYZRGBL  
PointXYZRGB  A point structure representing Euclidean xyz coordinates, and the RGB color 
PointXYZRGBL  
_PointXYZHSV  
PointXYZHSV  
PointXY  A 2D point structure representing Euclidean xy coordinates 
InterestPoint  A point structure representing an interest point with Euclidean xyz coordinates, and an interest value 
_Normal  A point structure representing normal coordinates and the surface curvature estimate 
Normal  
_Axis  A point structure representing an Axis using its normal coordinates 
Axis  
_PointNormal  A point structure representing Euclidean xyz coordinates, together with normal coordinates and the surface curvature estimate 
PointNormal  
_PointXYZRGBNormal  A point structure representing Euclidean xyz coordinates, and the RGB color, together with normal coordinates and the surface curvature estimate 
PointXYZRGBNormal  
_PointXYZINormal  A point structure representing Euclidean xyz coordinates, intensity, together with normal coordinates and the surface curvature estimate 
PointXYZINormal  
_PointWithRange  A point structure representing Euclidean xyz coordinates, padded with an extra range float 
PointWithRange  
_PointWithViewpoint  
PointWithViewpoint  A point structure representing Euclidean xyz coordinates together with the viewpoint from which it was seen 
MomentInvariants  A point structure representing the three moment invariants 
PrincipalRadiiRSD  A point structure representing the minimum and maximum surface radii (in meters) computed using RSD 
Boundary  A point structure representing a description of whether a point is lying on a surface boundary or not 
PrincipalCurvatures  A point structure representing the principal curvatures and their magnitudes 
PFHSignature125  A point structure representing the Point Feature Histogram (PFH) 
PFHRGBSignature250  A point structure representing the Point Feature Histogram with colors (PFHRGB) 
PPFSignature  A point structure for storing the Point Pair Feature (PPF) values 
PPFRGBSignature  A point structure for storing the Point Pair Color Feature (PPFRGB) values 
NormalBasedSignature12  A point structure representing the Normal Based Signature for a feature matrix of 4by3 
ShapeContext  A point structure representing a Shape Context 
SHOT  A point structure representing the generic Signature of Histograms of OrienTations (SHOT) 
SHOT352  A point structure representing the generic Signature of Histograms of OrienTations (SHOT)  shape only 
SHOT1344  A point structure representing the generic Signature of Histograms of OrienTations (SHOT)  shape+color 
_ReferenceFrame  A structure representing the Local Reference Frame of a point 
ReferenceFrame  
FPFHSignature33  A point structure representing the Fast Point Feature Histogram (FPFH) 
VFHSignature308  A point structure representing the Viewpoint Feature Histogram (VFH) 
ESFSignature640  A point structure representing the Ensemble of Shape Functions (ESF) 
GFPFHSignature16  A point structure representing the GFPFH descriptor with 16 bins 
Narf36  A point structure representing the Narf descriptor 
BorderDescription  A structure to store if a point in a range image lies on a border between an obstacle and the background 
IntensityGradient  A point structure representing the intensity gradient of an XYZI point cloud 
Histogram  A point structure representing an ND histogram 
_PointWithScale  A point structure representing a 3D position and scale 
PointWithScale  
_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 
PointSurfel  
ModelCoefficients  
PCLBase  PCL base class 
PCLBase< sensor_msgs::PointCloud2 >  
NdCopyEigenPointFunctor  Helper functor structure for copying data between an Eigen type and a PointT 
NdCopyPointEigenFunctor  Helper functor structure for copying data between an Eigen type and a PointT 
PointCloud  PointCloud represents the base class in PCL for storing collections of 3D points 
PointCloud< Eigen::MatrixXf >  PointCloud specialization for Eigen matrices 
PointRepresentation  PointRepresentation provides a set of methods for converting a point structs/object into an ndimensional vector 
DefaultPointRepresentation  DefaultPointRepresentation extends PointRepresentation to define default behavior for common point types 
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) 
DefaultPointRepresentation< PointXYZ >  
DefaultPointRepresentation< PointXYZI >  
DefaultPointRepresentation< PointNormal >  
DefaultPointRepresentation< PFHSignature125 >  
DefaultPointRepresentation< PFHRGBSignature250 >  
DefaultPointRepresentation< PPFSignature >  
DefaultPointRepresentation< FPFHSignature33 >  
DefaultPointRepresentation< VFHSignature308 >  
DefaultPointRepresentation< NormalBasedSignature12 >  
DefaultPointRepresentation< ShapeContext >  
DefaultPointRepresentation< SHOT352 >  
DefaultPointRepresentation< SHOT1344 >  
CustomPointRepresentation  CustomPointRepresentation extends PointRepresentation to allow for subpart selection on the point 
FieldMatches  
CopyIfFieldExists  A helper functor that can copy a specific value if the given field exists 
SetIfFieldExists  A helper functor that can set a specific value in a field if the field exists 
PointIndices  
PolygonMesh  
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 
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, ToFcameras), so that a conversion to point cloud and then to a spherical range image becomes unnecessary 
TexMaterial  
RGB  
TextureMesh  
Vertices  Describes a set of vertices in a polygon mesh, by basically storing an array of indices 
ShapeContext3DEstimation  ShapeContext3DEstimation implements the 3D shape context descriptor as described in: 
ShapeContext3DEstimation< PointInT, PointNT, Eigen::MatrixXf >  ShapeContext3DEstimation implements the 3D shape context descriptor as described in: 
BoundaryEstimation  BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle criterion 
BoundaryEstimation< PointInT, PointNT, Eigen::MatrixXf >  BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle criterion 
CVFHEstimation  CVFHEstimation estimates the Clustered Viewpoint Feature Histogram (CVFH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in: 
ESFEstimation  ESFEstimation estimates the ensemble of shape functions descriptors for a given point cloud dataset containing points 
Feature  Feature represents the base feature class 
FeatureFromNormals  
FeatureFromLabels  
FeatureWithLocalReferenceFrames  FeatureWithLocalReferenceFrames provides a public interface for descriptor extractor classes which need a local reference frame at each input keypoint 
FPFHEstimation  FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals 
FPFHEstimation< PointInT, PointNT, Eigen::MatrixXf >  FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals 
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 
IntegralImageTypeTraits  
IntegralImageTypeTraits< float >  
IntegralImageTypeTraits< char >  
IntegralImageTypeTraits< short >  
IntegralImageTypeTraits< unsigned short >  
IntegralImageTypeTraits< unsigned char >  
IntegralImageTypeTraits< int >  
IntegralImageTypeTraits< unsigned int >  
IntegralImage2D  Determines an integral image representation for a given organized data array 
IntegralImage2D< DataType, 1 >  Partial template specialization for integral images with just one channel 
IntegralImageNormalEstimation  Surface normal estimation on organized data using integral images 
IntensityGradientEstimation  IntensityGradientEstimation estimates the intensity gradient for a point cloud that contains position and intensity values 
IntensityGradientEstimation< PointInT, PointNT, Eigen::MatrixXf >  IntensityGradientEstimation estimates the intensity gradient for a point cloud that contains position and intensity values 
IntensitySpinEstimation  IntensitySpinEstimation estimates the intensitydomain spin image descriptors for a given point cloud dataset containing points and intensity 
IntensitySpinEstimation< PointInT, Eigen::MatrixXf >  IntensitySpinEstimation estimates the intensitydomain spin image descriptors for a given point cloud dataset containing points and intensity 
MomentInvariantsEstimation  MomentInvariantsEstimation estimates the 3 moment invariants (j1, j2, j3) at each 3D point 
MomentInvariantsEstimation< PointInT, Eigen::MatrixXf >  MomentInvariantsEstimation estimates the 3 moment invariants (j1, j2, j3) at each 3D point 
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 
Narf  NARF (Normal Aligned Radial Features) is a point feature descriptor type for 3D data 
FeaturePointRepresentation  
NarfDescriptor  Computes NARF feature descriptors for points in a range image 
Parameters  
NormalEstimation  NormalEstimation estimates local surface properties (surface normals and curvatures)at each 3D point 
NormalEstimation< PointInT, Eigen::MatrixXf >  NormalEstimation estimates local surface properties at each 3D point, such as surface normals and curvatures 
NormalEstimationOMP  NormalEstimationOMP estimates local surface properties at each 3D point, such as surface normals and curvatures, in parallel, using the OpenMP standard 
NormalEstimationOMP< PointInT, Eigen::MatrixXf >  NormalEstimationOMP estimates local surface properties at each 3D point, such as surface normals and curvatures, in parallel, using the OpenMP standard 
NormalBasedSignatureEstimation  Normalbased feature signature estimation class 
PFHEstimation  PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals 
PFHEstimation< PointInT, PointNT, Eigen::MatrixXf >  PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals 
PFHRGBEstimation  
PPFEstimation  Class that calculates the "surflet" features for each pair in the given pointcloud 
PPFEstimation< PointInT, PointNT, Eigen::MatrixXf >  Class that calculates the "surflet" features for each pair in the given pointcloud 
PPFRGBEstimation  
PPFRGBRegionEstimation  
PrincipalCurvaturesEstimation  PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals 
PrincipalCurvaturesEstimation< PointInT, PointNT, Eigen::MatrixXf >  PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals 
RangeImageBorderExtractor  Extract obstacle borders from range images, meaning positions where there is a transition from foreground to background 
LocalSurface  Stores some information extracted from the neighborhood of a point 
Parameters  Parameters used in this class 
ShadowBorderIndices  Stores the indices of the shadow border corresponding to obstacle borders 
RIFTEstimation  RIFTEstimation estimates the Rotation Invariant Feature Transform descriptors for a given point cloud dataset containing points and intensity 
RIFTEstimation< PointInT, GradientT, Eigen::MatrixXf >  RIFTEstimation estimates the Rotation Invariant Feature Transform descriptors for a given point cloud dataset containing points and intensity 
RSDEstimation  RSDEstimation estimates the Radiusbased Surface Descriptor (minimal and maximal radius of the local surface's curves) for a given point cloud dataset containing points and normals 
SHOTEstimationBase  SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals 
SHOTEstimation  SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals 
SHOTEstimation< PointInT, PointNT, Eigen::MatrixXf, PointRFT >  SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals 
SHOTColorEstimation  SHOTColorEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points, normals and colors 
SHOTColorEstimation< PointInT, PointNT, Eigen::MatrixXf, PointRFT >  
SHOTLocalReferenceFrameEstimation  SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor 
SHOTLocalReferenceFrameEstimationOMP  SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor 
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 
SHOTColorEstimationOMP  
SpinImageEstimation  Estimates spinimage descriptors in the given input points 
SpinImageEstimation< PointInT, PointNT, Eigen::MatrixXf >  Estimates spinimage descriptors in the given input points 
StatisticalMultiscaleInterestRegionExtraction  Class for extracting interest regions from unstructured point clouds, based on a multi scale statistical approach 
UniqueShapeContext  UniqueShapeContext implements the Unique Shape Descriptor described here: 
UniqueShapeContext< PointInT, Eigen::MatrixXf, PointRFT >  UniqueShapeContext implements the Unique Shape Descriptor described here: 
VFHEstimation  VFHEstimation estimates the Viewpoint Feature Histogram (VFH) descriptor for a given point cloud dataset containing points and normals 
xNdCopyEigenPointFunctor  Helper functor structure for copying data between an Eigen::VectorXf and a PointT 
xNdCopyPointEigenFunctor  Helper functor structure for copying data between an Eigen::VectorXf and a PointT 
ApproximateVoxelGrid  ApproximateVoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data 
BilateralFilter  A bilateral filter implementation for point cloud data 
Clipper3D  Base class for 3D clipper objects 
PointDataAtOffset  A datatype that enables typecorrect comparisons 
ComparisonBase  The (abstract) base class for the comparison object 
FieldComparison  The fieldbased specialization of the comparison object 
PackedRGBComparison  A packed rgb specialization of the comparison object 
PackedHSIComparison  A packed HSI specialization of the comparison object 
TfQuadraticXYZComparison  A comparison whether the (x,y,z) components of a given point satisfy (p'Ap + 2v'p + c [OP] 0) 
ConditionBase  Base condition class 
ConditionAnd  AND condition 
ConditionOr  OR condition 
ConditionalRemoval  ConditionalRemoval filters data that satisfies certain conditions 
CropBox  CropBox is a filter that allows the user to filter all the data inside of a given box 
CropBox< sensor_msgs::PointCloud2 >  CropBox is a filter that allows the user to filter all the data inside of a given box 
CropHull  Filter points that lie inside or outside a 3D closed surface or 2D closed polygon, as generated by the ConvexHull or ConcaveHull classes 
ExtractIndices  ExtractIndices extracts a set of indices from a point cloud 
ExtractIndices< sensor_msgs::PointCloud2 >  ExtractIndices extracts a set of indices from a point cloud 
Filter  Filter represents the base filter class 
Filter< sensor_msgs::PointCloud2 >  Filter represents the base filter class 
FilterIndices  FilterIndices represents the base class for filters that are about binary point removal 
FilterIndices< sensor_msgs::PointCloud2 >  FilterIndices represents the base class for filters that are about binary point removal 
NormalSpaceSampling  NormalSpaceSampling samples the input point cloud in the space of normal directions computed at every point 
PassThrough  PassThrough passes points in a cloud based on constraints for one particular field of the point type 
PassThrough< sensor_msgs::PointCloud2 >  PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints 
PlaneClipper3D  Implementation of a plane clipper in 3D 
ProjectInliers  ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud 
ProjectInliers< sensor_msgs::PointCloud2 >  ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud 
RadiusOutlierRemoval  RadiusOutlierRemoval filters points in a cloud based on the number of neighbors they have 
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 
RandomSample  RandomSample applies a random sampling with uniform probability 
RandomSample< sensor_msgs::PointCloud2 >  RandomSample applies a random sampling with uniform probability 
StatisticalOutlierRemoval  StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data 
StatisticalOutlierRemoval< sensor_msgs::PointCloud2 >  StatisticalOutlierRemoval uses point neighborhood statistics to filter outlier data 
VoxelGrid  VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data 
VoxelGrid< sensor_msgs::PointCloud2 >  VoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data 
LineIterator  Organized Index Iterator for iterating over the "pixels" for a given line using the Bresenham algorithm 
OrganizedIndexIterator  Base class for iterators on 2dimensional maps like images/organized clouds etc 
PlanarPolygon  PlanarPolygon represents a planar (2D) polygon, potentially in a 3D space 
AdaptiveRangeCoder  AdaptiveRangeCoder compression class 
StaticRangeCoder  StaticRangeCoder compression class 
FileReader  Point Cloud Data (FILE) file format reader interface 
FileWriter  Point Cloud Data (FILE) file format writer 
Grabber  Grabber interface for PCL 1.x device drivers 
PCDGrabberBase  Base class for PCD file grabber 
PCDGrabber  
PCDReader  Point Cloud Data (PCD) file format reader 
PCDWriter  Point Cloud Data (PCD) file format writer 
PCLIOException  Base exception class for I/O operations 
PLYReader  Point Cloud Data (PLY) file format reader 
PLYWriter  Point Cloud Data (PLY) file format writer 
KdTree  KdTree represents the base spatial locator class for kdtree implementations 
KdTreeFLANN  KdTreeFLANN is a generic type of 3D spatial locator using kDtree structures 
KdTreeFLANN< Eigen::MatrixXf >  KdTreeFLANN is a generic type of 3D spatial locator using kDtree structures 
HarrisKeypoint3D  HarrisKeypoint3D uses the idea of 2D Harris keypoints, but instead of using image gradients, it uses surface normals 
Keypoint  Keypoint represents the base class for key points 
NarfKeypoint  NARF (Normal Aligned Radial Feature) keypoints 
Parameters  Parameters used in this class 
SIFTKeypointFieldSelector  
SIFTKeypointFieldSelector< PointNormal >  
SIFTKeypointFieldSelector< PointXYZRGB >  
SIFTKeypointFieldSelector< PointXYZRGBA >  
SIFTKeypoint  SIFTKeypoint detects the Scale Invariant Feature Transform keypoints for a given point cloud dataset containing points and intensity 
SmoothedSurfacesKeypoint  Based on the paper: Xinju Li and Igor Guskov Multiscale features for approximate alignment of pointbased surfaces Proceedings of the third Eurographics symposium on Geometry processing July 2005, Vienna, Austria 
UniformSampling  UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data 
Leaf  Simple structure to hold an nD centroid and the number of points in a leaf 
SolverDidntConvergeException  An exception that is thrown when the non linear solver didn't converge 
NotEnoughPointsException  An exception that is thrown when the number of correspondants is not equal to the minimum required 
GeneralizedIterativeClosestPoint  GeneralizedIterativeClosestPoint is an ICP variant that implements the generalized iterative closest point algorithm as described by Alex Segal et al 
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 
ErrorFunctor  
HuberPenalty  
TruncatedError  
IterativeClosestPoint  IterativeClosestPoint provides a base implementation of the Iterative Closest Point algorithm 
IterativeClosestPointNonLinear  IterativeClosestPointNonLinear is an ICP variant that uses LevenbergMarquardt optimization backend 
PPFHashMapSearch  
HashKeyStruct  Data structure to hold the information for the key in the feature hash map of the PPFHashMapSearch class 
PPFRegistration  Class that registers two point clouds based on their sets of PPFSignatures 
PoseWithVotes  Structure for storing a pose (represented as an Eigen::Affine3f) and an integer for counting votes 
PyramidFeatureHistogram  Class that compares two sets of features by using a multiscale representation of the features inside a pyramid 
Registration  Registration represents the base registration class 
WarpPointRigid  
WarpPointRigid3D  
WarpPointRigid6D  
LeastMedianSquares  LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm 
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 
MEstimatorSampleConsensus  MEstimatorSampleConsensus represents an implementation of the MSAC (Mestimator SAmple Consensus) algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S 
ProgressiveSampleConsensus  RandomSampleConsensus represents an implementation of the RANSAC (RAndom SAmple Consensus) algorithm, as described in: "Matching with PROSAC – Progressive Sample Consensus", Chum, O 
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 
RandomizedMEstimatorSampleConsensus  RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized Mestimator SAmple Consensus) algorithm, which basically adds a Td,d test (see RandomizedRandomSampleConsensus) to an MSAC estimator (see MEstimatorSampleConsensus) 
RandomizedRandomSampleConsensus  RandomizedRandomSampleConsensus represents an implementation of the RRANSAC (Randomized RAndom SAmple Consensus), as described in "Randomized RANSAC with Td,d test", O 
SampleConsensus  SampleConsensus represents the base class 
SampleConsensusModel  SampleConsensusModel represents the base model class 
SampleConsensusModelFromNormals  SampleConsensusModelFromNormals represents the base model class for models that require the use of surface normals for estimation 
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 
SampleConsensusModelCircle2D  SampleConsensusModelCircle2D defines a model for 2D circle segmentation on the XY plane 
SampleConsensusModelCone  SampleConsensusModelCone defines a model for 3D cone segmentation 
SampleConsensusModelCylinder  SampleConsensusModelCylinder defines a model for 3D cylinder segmentation 
SampleConsensusModelLine  SampleConsensusModelLine defines a model for 3D line segmentation 
SampleConsensusModelNormalParallelPlane  SampleConsensusModelNormalParallelPlane defines a model for 3D plane segmentation using additional surface normal constraints 
SampleConsensusModelNormalPlane  SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints 
SampleConsensusModelNormalSphere  SampleConsensusModelNormalSphere defines a model for 3D sphere segmentation using additional surface normal constraints 
SampleConsensusModelParallelLine  SampleConsensusModelParallelLine defines a model for 3D line segmentation using additional angular constraints 
SampleConsensusModelParallelPlane  SampleConsensusModelParallelPlane defines a model for 3D plane segmentation using additional angular constraints 
SampleConsensusModelPerpendicularPlane  SampleConsensusModelPerpendicularPlane defines a model for 3D plane segmentation using additional angular constraints 
SampleConsensusModelPlane  SampleConsensusModelPlane defines a model for 3D plane segmentation 
SampleConsensusModelRegistration  SampleConsensusModelRegistration defines a model for PointToPoint registration outlier rejection 
SampleConsensusModelSphere  SampleConsensusModelSphere defines a model for 3D sphere segmentation 
SampleConsensusModelStick  SampleConsensusModelStick defines a model for 3D stick segmentation 
Comparator  Comparator is the base class for comparators that compare two points given some function 
EdgeAwarePlaneComparator  EdgeAwarePlaneComparator is a Comparator that operates on plane coefficients, for use in planar segmentation 
EuclideanClusterComparator  EuclideanClusterComparator is a comparator used for finding clusters supported by planar surfaces 
EuclideanPlaneCoefficientComparator  EuclideanPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation 
EuclideanClusterExtraction  EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense 
LabeledEuclideanClusterExtraction  LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, with label info 
ExtractPolygonalPrismData  ExtractPolygonalPrismData uses a set of point indices that represent a planar model, and together with a given height, generates a 3D polygonal prism 
OrganizedConnectedComponentSegmentation  OrganizedConnectedComponentSegmentation allows connected components to be found within organized point cloud data, given a comparison function 
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 
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 
PlanarRegion  PlanarRegion represents a set of points that lie in a plane 
PlaneCoefficientComparator  PlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation 
PlaneRefinementComparator  PlaneRefinementComparator is a Comparator that operates on plane coefficients, for use in planar segmentation 
Region3D  Region3D represents summary statistics of a 3D collection of points 
RGBPlaneCoefficientComparator  RGBPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation 
SACSegmentation  SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models, in the sense that it just creates a Nodelet wrapper for genericpurpose SACbased segmentation 
SACSegmentationFromNormals  SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation 
SegmentDifferences  SegmentDifferences obtains the difference between two spatially aligned point clouds and returns the difference between them for a maximum given distance threshold 
BilateralUpsampling  Bilateral filtering implementation, based on the following paper: 
EarClipping  The ear clipping triangulation algorithm 
GreedyProjectionTriangulation  GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections 
GridProjection  Grid projection surface reconstruction method 
Leaf  Data leaf 
MarchingCubes  The marching cubes surface reconstruction algorithm 
MarchingCubesHoppe  The marching cubes surface reconstruction algorithm, using a signed distance function based on the distance from tangent planes, proposed by Hoppe et 
MarchingCubesRBF  The marching cubes surface reconstruction algorithm, using a signed distance function based on radial basis functions 
MovingLeastSquares  MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation 
MLSResult  Data structure used to store the results of the MLS fitting 
MLSVoxelGrid  A minimalistic implementation of a voxel grid, necessary for the point cloud upsampling 
Leaf  
MovingLeastSquaresOMP  MovingLeastSquaresOMP represent an OpenMP implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation 
OrganizedFastMesh  Simple triangulation/surface reconstruction for organized point clouds 
Poisson  The Poisson surface reconstruction algorithm 
CloudSurfaceProcessing  CloudSurfaceProcessing represents the base class for algorithms that take a point cloud as an input and produce a new output cloud that has been modified towards a better surface representation 
MeshProcessing  MeshProcessing represents the base class for mesh processing algorithms 
PCLSurfaceBase  Pure abstract class 
SurfaceReconstruction  SurfaceReconstruction represents a base surface reconstruction class 
MeshConstruction  MeshConstruction represents a base surface reconstruction class 
SurfelSmoothing  
TextureMapping  The texture mapping algorithm 
MeshSmoothingLaplacianVTK  PCL mesh smoothing based on the vtkSmoothPolyDataFilter algorithm from the VTK library 
MeshSmoothingWindowedSincVTK  PCL mesh smoothing based on the vtkWindowedSincPolyDataFilter algorithm from the VTK library 
MeshSubdivisionVTK  PCL mesh smoothing based on the vtkLinearSubdivisionFilter, vtkLoopSubdivisionFilter, vtkButterflySubdivisionFilter depending on the selected MeshSubdivisionVTKFilterType algorithm from the VTK library 
VTKUtils  
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 
sensor_msgs  
Image  
PointCloud2  
PointField  
std  
std_msgs  
Header  
Ui  
cloud_point_index_idx  
Mesh  
ObjectFeatures  
ObjectModel  
ObjectRecognition  
ObjectRecognitionParameters  
OpenNICapture  
OpenNIPassthrough  
OrganizedSegmentationDemo 
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Pages generated on Mon Jul 23 2012 08:33:18