pcl Namespace Reference

Namespaces
namespace	common
namespace	ComparisonOps
namespace	console
namespace	detail
namespace	distances
namespace	fields
namespace	geometry
namespace	io
namespace	octree
namespace	registration
namespace	search
namespace	surface
namespace	test
	test_macros.h provide helper macros for testing vectors, matrices etc.
namespace	texture_mapping
namespace	traits
namespace	utils
namespace	visualization
Classes
class	ChannelProperties
	ChannelProperties stores the properties of each channel in a cloud, namely: More...
class	CloudProperties
	CloudProperties stores a list of optional point cloud properties such as: 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	GaussianKernel
	Class GaussianKernel assembles all the method for computing, convolving, smoothing, gradients computing an image using a gaussian kernel. More...
class	PCA
	Principal Component analysis (PCA) class. More...
class	PiecewiseLinearFunction
	This provides functionalities to efficiently return values for piecewise linear function. More...
class	PolynomialCalculationsT
	This provides some functionality for polynomials, like finding roots or approximating bivariate polynomials. More...
class	PosesFromMatches
	calculate 3D transformation based on point correspondencdes More...
class	Synchronizer
	/brief This template class synchronizes two data streams of different types. More...
class	StopWatch
	Simple stopwatch. More...
class	ScopeTime
	Class to measure the time spent in a scope. More...
class	TimeTrigger
	Timer class that invokes registered callback methods periodically. More...
class	TransformationFromCorrespondences
	Calculates a transformation based on corresponding 3D points. More...
class	VectorAverage
	Calculates the weighted average and the covariance matrix. More...
struct	Correspondence
	Correspondence represents a match between two entities (e.g., points, descriptors, etc). More...
struct	PointCorrespondence3D
	Representation of a (possible) correspondence between two 3D points in two different coordinate frames (e.g. More...
struct	PointCorrespondence6D
	Representation of a (possible) correspondence between two points (e.g. More...
class	PCLException
	A base class for all pcl exceptions which inherits from std::runtime_error. More...
class	InvalidConversionException
	An exception that is thrown when a 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...
class	InitFailedException
	An exception thrown when init can not be performed should be used in all the PCLBase class inheritants. More...
class	UnorganizedPointCloudException
	An exception that is thrown when an organized point cloud is needed but not provided. More...
class	KernelWidthTooSmallException
	An exception that is thrown when the kernel size is too small. More...
class	UnhandledPointTypeException
class	ComputeFailedException
struct	for_each_type_impl
struct	for_each_type_impl< false >
struct	intersect
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	PointXYZI
struct	_PointXYZL
struct	PointXYZL
struct	Label
struct	_PointXYZRGBA
	A point structure representing Euclidean xyz coordinates, and the RGBA color. More...
struct	PointXYZRGBA
struct	_PointXYZRGB
struct	_PointXYZRGBL
struct	PointXYZRGB
	A point structure representing Euclidean xyz coordinates, and the RGB color. More...
struct	PointXYZRGBL
struct	_PointXYZHSV
struct	PointXYZHSV
struct	PointXY
	A 2D point structure representing Euclidean xy coordinates. More...
struct	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	Normal
struct	_Axis
	A point structure representing an Axis using its normal coordinates. More...
struct	Axis
struct	_PointNormal
	A point structure representing Euclidean xyz coordinates, together with normal coordinates and the surface curvature estimate. More...
struct	PointNormal
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	PointXYZINormal
struct	_PointWithRange
	A point structure representing Euclidean xyz coordinates, padded with an extra range float. More...
struct	PointWithRange
struct	_PointWithViewpoint
struct	PointWithViewpoint
	A point structure representing Euclidean xyz coordinates together with the viewpoint from which it was seen. More...
struct	MomentInvariants
	A point structure representing the three moment invariants. More...
struct	PrincipalRadiiRSD
	A point structure representing the minimum and maximum surface radii (in meters) computed using RSD. More...
struct	Boundary
	A point structure representing a description of whether a point is lying on a surface boundary or not. More...
struct	PrincipalCurvatures
	A point structure representing the principal curvatures and their magnitudes. More...
struct	PFHSignature125
	A point structure representing the Point Feature Histogram (PFH). More...
struct	PFHRGBSignature250
	A point structure representing the Point Feature Histogram with colors (PFHRGB). More...
struct	PPFSignature
	A point structure for storing the Point Pair Feature (PPF) values. More...
struct	PPFRGBSignature
	A point structure for storing the Point Pair Color Feature (PPFRGB) values. More...
struct	NormalBasedSignature12
	A point structure representing the Normal Based Signature for a feature matrix of 4-by-3. More...
struct	ShapeContext
	A point structure representing a Shape Context. More...
struct	SHOT
	A point structure representing the generic Signature of Histograms of OrienTations (SHOT). More...
struct	SHOT352
	A point structure representing the generic Signature of Histograms of OrienTations (SHOT) - shape only. More...
struct	SHOT1344
	A point structure representing the generic Signature of Histograms of OrienTations (SHOT) - shape+color. More...
struct	_ReferenceFrame
	A structure representing the Local Reference Frame of a point. More...
struct	ReferenceFrame
struct	FPFHSignature33
	A point structure representing the Fast Point Feature Histogram (FPFH). More...
struct	VFHSignature308
	A point structure representing the Viewpoint Feature Histogram (VFH). More...
struct	ESFSignature640
	A point structure representing the Ensemble of Shape Functions (ESF). More...
struct	GFPFHSignature16
	A point structure representing the GFPFH descriptor with 16 bins. More...
struct	Narf36
	A point structure representing the Narf descriptor. More...
struct	BorderDescription
	A structure to store if a point in a range image lies on a border between an obstacle and the background. More...
struct	IntensityGradient
	A point structure representing the intensity gradient of an XYZI point cloud. More...
struct	Histogram
	A point structure representing an N-D histogram. More...
struct	_PointWithScale
	A point structure representing a 3-D position and scale. More...
struct	PointWithScale
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	PointSurfel
struct	ModelCoefficients
class	PCLBase
	PCL base class. More...
class	PCLBase< sensor_msgs::PointCloud2 >
struct	NdCopyEigenPointFunctor
	Helper functor structure for copying data between an Eigen type and a PointT. More...
struct	NdCopyPointEigenFunctor
	Helper functor structure for copying data between an Eigen type and a PointT. More...
class	PointCloud
	PointCloud represents the base class in PCL for storing collections of 3D points. More...
class	PointCloud< Eigen::MatrixXf >
	PointCloud specialization for Eigen matrices. More...
class	PointRepresentation
	PointRepresentation provides a set of methods for converting a point structs/object into an n-dimensional vector. More...
class	DefaultPointRepresentation
	DefaultPointRepresentation extends PointRepresentation to define default behavior for common point types. More...
class	DefaultFeatureRepresentation
	DefaulFeatureRepresentation extends PointRepresentation and is intended to be used when defining the default behavior for feature descriptor types (i.e., copy each element of each field into a float array). More...
class	DefaultPointRepresentation< PointXYZ >
class	DefaultPointRepresentation< PointXYZI >
class	DefaultPointRepresentation< PointNormal >
class	DefaultPointRepresentation< PFHSignature125 >
class	DefaultPointRepresentation< PFHRGBSignature250 >
class	DefaultPointRepresentation< PPFSignature >
class	DefaultPointRepresentation< FPFHSignature33 >
class	DefaultPointRepresentation< VFHSignature308 >
class	DefaultPointRepresentation< NormalBasedSignature12 >
class	DefaultPointRepresentation< ShapeContext >
class	DefaultPointRepresentation< SHOT352 >
class	DefaultPointRepresentation< SHOT1344 >
class	CustomPointRepresentation
	CustomPointRepresentation extends PointRepresentation to allow for sub-part selection on the point. More...
struct	FieldMatches
struct	CopyIfFieldExists
	A helper functor that can copy a specific value if the given field exists. More...
struct	SetIfFieldExists
	A helper functor that can set a specific value in a field if the field exists. More...
struct	PointIndices
struct	PolygonMesh
class	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...
struct	TexMaterial
struct	TextureMesh
struct	Vertices
	Describes a set of vertices in a polygon mesh, by basically storing an array of indices. More...
class	ShapeContext3DEstimation
	ShapeContext3DEstimation implements the 3D shape context descriptor as described in: More...
class	ShapeContext3DEstimation< PointInT, PointNT, Eigen::MatrixXf >
	ShapeContext3DEstimation implements the 3D shape context descriptor as described in: More...
class	BoundaryEstimation
	BoundaryEstimation estimates whether a set of points is lying on surface boundaries using an angle criterion. More...
class	BoundaryEstimation< PointInT, PointNT, Eigen::MatrixXf >
	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 XYZ data and normals, as presented in: More...
class	ESFEstimation
	ESFEstimation estimates the ensemble of shape functions descriptors for a given point cloud dataset containing points. More...
class	Feature
	Feature represents the base feature class. More...
class	FeatureFromNormals
class	FeatureFromLabels
class	FeatureWithLocalReferenceFrames
	FeatureWithLocalReferenceFrames provides a public interface for descriptor extractor classes which need a local reference frame at each input keypoint. More...
class	FPFHEstimation
	FPFHEstimation estimates the Fast Point Feature Histogram (FPFH) descriptor for a given point cloud dataset containing points and normals. More...
class	FPFHEstimation< PointInT, PointNT, Eigen::MatrixXf >
	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...
struct	IntegralImageTypeTraits
struct	IntegralImageTypeTraits< float >
struct	IntegralImageTypeTraits< char >
struct	IntegralImageTypeTraits< short >
struct	IntegralImageTypeTraits< unsigned short >
struct	IntegralImageTypeTraits< unsigned char >
struct	IntegralImageTypeTraits< int >
struct	IntegralImageTypeTraits< unsigned int >
class	IntegralImage2D
	Determines an integral image representation for a given organized data array. More...
class	IntegralImage2D< DataType, 1 >
	partial template specialization for integral images with just one channel. More...
class	IntegralImageNormalEstimation
	Surface normal estimation on organized data using integral images. More...
class	IntensityGradientEstimation
	IntensityGradientEstimation estimates the intensity gradient for a point cloud that contains position and intensity values. More...
class	IntensityGradientEstimation< PointInT, PointNT, Eigen::MatrixXf >
	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	IntensitySpinEstimation< PointInT, Eigen::MatrixXf >
	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	MomentInvariantsEstimation< PointInT, Eigen::MatrixXf >
	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 (surface normals and curvatures)at each 3D point. More...
class	NormalEstimation< PointInT, Eigen::MatrixXf >
	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	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. More...
class	NormalBasedSignatureEstimation
	Normal-based feature signature estimation class. More...
class	PFHEstimation
	PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals. More...
class	PFHEstimation< PointInT, PointNT, Eigen::MatrixXf >
	PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals. More...
class	PFHRGBEstimation
class	PPFEstimation
	Class that calculates the "surflet" features for each pair in the given pointcloud. More...
class	PPFEstimation< PointInT, PointNT, Eigen::MatrixXf >
	Class that calculates the "surflet" features for each pair in the given pointcloud. More...
class	PPFRGBEstimation
class	PPFRGBRegionEstimation
class	PrincipalCurvaturesEstimation
	PrincipalCurvaturesEstimation estimates the directions (eigenvectors) and magnitudes (eigenvalues) of principal surface curvatures for a given point cloud dataset containing points and normals. More...
class	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. 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	RIFTEstimation< PointInT, GradientT, Eigen::MatrixXf >
	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< 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. More...
class	SHOTColorEstimation
	SHOTColorEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points, normals and colors. More...
class	SHOTColorEstimation< PointInT, PointNT, Eigen::MatrixXf, PointRFT >
class	SHOTLocalReferenceFrameEstimation
	SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor. More...
class	SHOTLocalReferenceFrameEstimationOMP
	SHOTLocalReferenceFrameEstimation estimates the Local Reference Frame used in the calculation of the (SHOT) descriptor. More...
class	SHOTEstimationOMP
	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	SHOTColorEstimationOMP
class	SpinImageEstimation
	Estimates spin-image descriptors in the given input points. More...
class	SpinImageEstimation< PointInT, PointNT, Eigen::MatrixXf >
	Estimates spin-image descriptors in the given input points. More...
class	StatisticalMultiscaleInterestRegionExtraction
	Class for extracting interest regions from unstructured point clouds, based on a multi scale statistical approach. More...
class	UniqueShapeContext
	UniqueShapeContext implements the Unique Shape Descriptor described here: More...
class	UniqueShapeContext< PointInT, Eigen::MatrixXf, PointRFT >
	UniqueShapeContext implements the Unique Shape Descriptor described here: More...
class	VFHEstimation
	VFHEstimation estimates the Viewpoint Feature Histogram (VFH) descriptor for a given point cloud dataset containing points and normals. More...
struct	xNdCopyEigenPointFunctor
	Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More...
struct	xNdCopyPointEigenFunctor
	Helper functor structure for copying data between an Eigen::VectorXf and a PointT. More...
class	ApproximateVoxelGrid
	ApproximateVoxelGrid assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
class	BilateralFilter
	A bilateral filter implementation for point cloud data. More...
class	Clipper3D
	Base class for 3D clipper objects. More...
class	PointDataAtOffset
	A datatype that enables type-correct comparisons. More...
class	ComparisonBase
	The (abstract) base class for the comparison object. More...
class	FieldComparison
	The field-based specialization of the comparison object. More...
class	PackedRGBComparison
	A packed rgb specialization of the comparison object. More...
class	PackedHSIComparison
	A packed HSI specialization of the comparison object. More...
class	TfQuadraticXYZComparison
	A comparison whether the (x,y,z) components of a given point satisfy (p'Ap + 2v'p + c [OP] 0). More...
class	ConditionBase
	Base condition class. More...
class	ConditionAnd
	AND condition. More...
class	ConditionOr
	OR condition. More...
class	ConditionalRemoval
	ConditionalRemoval filters data that satisfies certain conditions. More...
class	CropBox
	CropBox is a filter that allows the user to filter all the data inside of a given box. More...
class	CropBox< sensor_msgs::PointCloud2 >
	CropBox is a filter that allows the user to filter all the data inside of a given box. More...
class	CropHull
	Filter points that lie inside or outside a 3D closed surface or 2D closed polygon, as generated by the ConvexHull or ConcaveHull classes. More...
class	ExtractIndices
	ExtractIndices extracts a set of indices from a point cloud. More...
class	ExtractIndices< sensor_msgs::PointCloud2 >
	ExtractIndices extracts a set of indices from a point cloud. More...
class	Filter
	Filter represents the base filter class. More...
class	Filter< sensor_msgs::PointCloud2 >
	Filter represents the base filter class. More...
class	FilterIndices
	FilterIndices represents the base class for filters that are about binary point removal. More...
class	FilterIndices< sensor_msgs::PointCloud2 >
	FilterIndices represents the base class for filters that are about binary point removal. More...
class	NormalSpaceSampling
	NormalSpaceSampling samples the input point cloud in the space of normal directions computed at every point. More...
class	PassThrough
	PassThrough passes points in a cloud based on constraints for one particular field of the point type. More...
class	PassThrough< sensor_msgs::PointCloud2 >
	PassThrough uses the base Filter class methods to pass through all data that satisfies the user given constraints. More...
class	PlaneClipper3D
	Implementation of a plane clipper in 3D. More...
class	ProjectInliers
	ProjectInliers uses a model and a set of inlier indices from a PointCloud to project them into a separate PointCloud. More...
class	ProjectInliers< 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 filters points in a cloud based on the number of neighbors they have. 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	RandomSample
	RandomSample applies a random sampling with uniform probability. More...
class	RandomSample< sensor_msgs::PointCloud2 >
	RandomSample applies a random sampling with uniform probability. 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...
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	LineIterator
	Organized Index Iterator for iterating over the "pixels" for a given line using the Bresenham algorithm. More...
class	OrganizedIndexIterator
	base class for iterators on 2-dimensional maps like images/organized clouds etc. More...
class	PlanarPolygon
	PlanarPolygon represents a planar (2D) polygon, potentially in a 3D space. More...
class	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	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
	Base exception class for I/O operations. 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 kd-tree implementations. More...
class	KdTreeFLANN
	KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. More...
class	KdTreeFLANN< Eigen::MatrixXf >
	KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. More...
class	HarrisKeypoint3D
	HarrisKeypoint3D uses the idea of 2D Harris keypoints, but instead of using image gradients, it uses surface normals. 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 >
struct	SIFTKeypointFieldSelector< PointXYZRGBA >
class	SIFTKeypoint
	SIFTKeypoint detects the Scale Invariant Feature Transform keypoints for a given point cloud dataset containing points and intensity. More...
class	SmoothedSurfacesKeypoint
	Based on the paper: Xinju Li and Igor Guskov Multi-scale features for approximate alignment of point-based surfaces Proceedings of the third Eurographics symposium on Geometry processing July 2005, Vienna, Austria. More...
class	UniformSampling
	UniformSampling assembles a local 3D grid over a given PointCloud, and downsamples + filters the data. More...
class	SolverDidntConvergeException
	An exception that is thrown when the non linear solver didn't converge. More...
class	NotEnoughPointsException
	An exception that is thrown when the number of correspondants is not equal to the minimum required. More...
class	GeneralizedIterativeClosestPoint
	GeneralizedIterativeClosestPoint is an ICP variant that implements the generalized iterative closest point algorithm as described by Alex Segal et al. More...
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	PPFHashMapSearch
class	PPFRegistration
	Class that registers two point clouds based on their sets of PPFSignatures. More...
class	PyramidFeatureHistogram
	Class that compares two sets of features by using a multiscale representation of the features inside a pyramid. More...
class	Registration
	Registration represents the base registration class. 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...
struct	Functor
	Base functor all the models that need non linear optimization must define their own one and implement operator() (const Eigen::VectorXd& x, Eigen::VectorXd& fvec) or operator() (const Eigen::VectorXf& x, Eigen::VectorXf& fvec) dependening on the choosen _Scalar. More...
class	SampleConsensusModelCircle2D
	SampleConsensusModelCircle2D defines a model for 2D circle segmentation on the X-Y plane. More...
class	SampleConsensusModelCone
	SampleConsensusModelCone defines a model for 3D cone segmentation. More...
class	SampleConsensusModelCylinder
	SampleConsensusModelCylinder defines a model for 3D cylinder segmentation. More...
class	SampleConsensusModelLine
	SampleConsensusModelLine defines a model for 3D line segmentation. More...
class	SampleConsensusModelNormalParallelPlane
	SampleConsensusModelNormalParallelPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...
class	SampleConsensusModelNormalPlane
	SampleConsensusModelNormalPlane defines a model for 3D plane segmentation using additional surface normal constraints. More...
class	SampleConsensusModelNormalSphere
	SampleConsensusModelNormalSphere defines a model for 3D sphere segmentation using additional surface normal constraints. More...
class	SampleConsensusModelParallelLine
	SampleConsensusModelParallelLine defines a model for 3D line segmentation using additional angular constraints. More...
class	SampleConsensusModelParallelPlane
	SampleConsensusModelParallelPlane defines a model for 3D plane segmentation using additional angular constraints. More...
class	SampleConsensusModelPerpendicularPlane
	SampleConsensusModelPerpendicularPlane defines a model for 3D plane segmentation using additional angular constraints. More...
class	SampleConsensusModelPlane
	SampleConsensusModelPlane defines a model for 3D plane segmentation. More...
class	SampleConsensusModelRegistration
	SampleConsensusModelRegistration defines a model for Point-To-Point registration outlier rejection. More...
class	SampleConsensusModelSphere
	SampleConsensusModelSphere defines a model for 3D sphere segmentation. More...
class	SampleConsensusModelStick
	SampleConsensusModelStick defines a model for 3D stick segmentation. More...
class	Comparator
	Comparator is the base class for comparators that compare two points given some function. More...
class	EdgeAwarePlaneComparator
	EdgeAwarePlaneComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
class	EuclideanClusterComparator
	EuclideanClusterComparator is a comparator used for finding clusters supported by planar surfaces. More...
class	EuclideanPlaneCoefficientComparator
	EuclideanPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
class	EuclideanClusterExtraction
	EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense. More...
class	LabeledEuclideanClusterExtraction
	LabeledEuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense, with label info. More...
class	ExtractPolygonalPrismData
	ExtractPolygonalPrismData uses a set of point indices that represent a planar model, and together with a given height, generates a 3D polygonal prism. More...
class	OrganizedConnectedComponentSegmentation
	OrganizedConnectedComponentSegmentation allows connected components to be found within organized point cloud data, given a comparison function. More...
class	OrganizedMultiPlaneSegmentation
	OrganizedMultiPlaneSegmentation finds all planes present in the input cloud, and outputs a vector of plane equations, as well as a vector of point clouds corresponding to the inliers of each detected plane. More...
class	PlanarPolygonFusion
	PlanarPolygonFusion takes a list of 2D planar polygons and attempts to reduce them to a minimum set that best represents the scene, based on various given comparators. More...
class	PlanarRegion
	PlanarRegion represents a set of points that lie in a plane. More...
class	PlaneCoefficientComparator
	PlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
class	PlaneRefinementComparator
	PlaneRefinementComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
class	Region3D
	Region3D represents summary statistics of a 3D collection of points. More...
class	RGBPlaneCoefficientComparator
	RGBPlaneCoefficientComparator is a Comparator that operates on plane coefficients, for use in planar segmentation. More...
class	SACSegmentation
	SACSegmentation represents the Nodelet segmentation class for Sample Consensus methods and models, in the sense that it just creates a Nodelet wrapper for generic-purpose SAC-based segmentation. More...
class	SACSegmentationFromNormals
	SACSegmentationFromNormals represents the PCL nodelet segmentation class for Sample Consensus methods and models that require the use of surface normals for estimation. More...
class	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	BilateralUpsampling
	Bilateral filtering implementation, based on the following paper: * Kopf, Johannes and Cohen, Michael F. More...
class	EarClipping
	The ear clipping triangulation algorithm. More...
class	GreedyProjectionTriangulation
	GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections. More...
class	GridProjection
	Grid projection surface reconstruction method. More...
class	MarchingCubes
	The marching cubes surface reconstruction algorithm. More...
class	MarchingCubesHoppe
	The marching cubes surface reconstruction algorithm, using a signed distance function based on the distance from tangent planes, proposed by Hoppe et. More...
class	MarchingCubesRBF
	The marching cubes surface reconstruction algorithm, using a signed distance function based on radial basis functions. More...
class	MovingLeastSquares
	MovingLeastSquares represent an implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation. More...
class	MovingLeastSquaresOMP
	MovingLeastSquaresOMP represent an OpenMP implementation of the MLS (Moving Least Squares) algorithm for data smoothing and improved normal estimation. More...
class	OrganizedFastMesh
	Simple triangulation/surface reconstruction for organized point clouds. More...
class	Poisson
	The Poisson surface reconstruction algorithm. More...
class	CloudSurfaceProcessing
	CloudSurfaceProcessing represents the base class for algorithms that take a point cloud as an input and produce a new output cloud that has been modified towards a better surface representation. More...
class	MeshProcessing
	MeshProcessing represents the base class for mesh processing algorithms. More...
class	PCLSurfaceBase
	Pure abstract class. More...
class	SurfaceReconstruction
	SurfaceReconstruction represents a base surface reconstruction class. More...
class	MeshConstruction
	MeshConstruction represents a base surface reconstruction class. More...
class	SurfelSmoothing
class	TextureMapping
	The texture mapping algorithm. More...
class	MeshSmoothingLaplacianVTK
	PCL mesh smoothing based on the vtkSmoothPolyDataFilter algorithm from the VTK library. More...
class	MeshSmoothingWindowedSincVTK
	PCL mesh smoothing based on the vtkWindowedSincPolyDataFilter algorithm from the VTK library. More...
class	MeshSubdivisionVTK
	PCL mesh smoothing based on the vtkLinearSubdivisionFilter, vtkLoopSubdivisionFilter, vtkButterflySubdivisionFilter depending on the selected MeshSubdivisionVTKFilterType algorithm from the VTK library. More...
class	VTKUtils
class	RegistrationVisualizer
	RegistrationVisualizer represents the base class for rendering the intermediate positions 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 PolynomialCalculationsT < double >	PolynomialCalculationsd
typedef PolynomialCalculationsT< float >	PolynomialCalculations
typedef VectorAverage< float, 2 >	VectorAverage2f
typedef VectorAverage< float, 3 >	VectorAverage3f
typedef VectorAverage< float, 4 >	VectorAverage4f
typedef std::vector < pcl::Correspondence, Eigen::aligned_allocator < pcl::Correspondence > >	Correspondences
typedef boost::shared_ptr < Correspondences >	CorrespondencesPtr
typedef boost::shared_ptr < const Correspondences >	CorrespondencesConstPtr
typedef std::vector < PointCorrespondence3D, Eigen::aligned_allocator < PointCorrespondence3D > >	PointCorrespondences3DVector
typedef std::vector < PointCorrespondence6D, Eigen::aligned_allocator < PointCorrespondence6D > >	PointCorrespondences6DVector
typedef Eigen::Map < Eigen::Array3f >	Array3fMap
typedef const Eigen::Map < const Eigen::Array3f >	Array3fMapConst
typedef Eigen::Map < Eigen::Array4f, Eigen::Aligned >	Array4fMap
typedef const Eigen::Map < const Eigen::Array4f, Eigen::Aligned >	Array4fMapConst
typedef Eigen::Map < Eigen::Vector3f >	Vector3fMap
typedef const Eigen::Map < const Eigen::Vector3f >	Vector3fMapConst
typedef Eigen::Map < Eigen::Vector4f, Eigen::Aligned >	Vector4fMap
typedef const Eigen::Map < const Eigen::Vector4f, Eigen::Aligned >	Vector4fMapConst
typedef 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. More...
enum	SacModel {   SACMODEL_PLANE, SACMODEL_LINE, SACMODEL_CIRCLE2D, SACMODEL_CIRCLE3D,   SACMODEL_SPHERE, SACMODEL_CYLINDER, SACMODEL_CONE, SACMODEL_TORUS,   SACMODEL_PARALLEL_LINE, SACMODEL_PERPENDICULAR_PLANE, SACMODEL_PARALLEL_LINES, SACMODEL_NORMAL_PLANE,   SACMODEL_NORMAL_SPHERE, SACMODEL_REGISTRATION, SACMODEL_PARALLEL_PLANE, SACMODEL_NORMAL_PARALLEL_PLANE,   SACMODEL_STICK }
Functions
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.
float	normAngle (float alpha)
	Normalize an angle to (-PI, PI].
template<typename real >
std::ostream &	operator<< (std::ostream &os, const BivariatePolynomialT< real > &p)
template<typename PointT >
unsigned int	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 >
unsigned int	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 >
unsigned int	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 >
unsigned int	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 >
unsigned int	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 >
unsigned int	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 >
unsigned int	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 >
unsigned int	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 >
unsigned int	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 >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f &centroid)
	Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop.
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f &centroid)
	Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop.
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3f &covariance_matrix, Eigen::Vector4f &centroid)
	Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop.
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d &centroid)
	Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop.
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d &centroid)
	Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop.
template<typename PointT >
unsigned int	computeMeanAndCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3d &covariance_matrix, Eigen::Vector4d &centroid)
	Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop.
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3f &covariance_matrix)
	Compute the normalized 3x3 covariance matrix for a already demeaned point cloud.
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix3f &covariance_matrix)
	Compute the normalized 3x3 covariance matrix for a already demeaned point cloud.
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3f &covariance_matrix)
	Compute the normalized 3x3 covariance matrix for a already demeaned point cloud.
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, Eigen::Matrix3d &covariance_matrix)
	Compute the normalized 3x3 covariance matrix for a already demeaned point cloud.
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const std::vector< int > &indices, Eigen::Matrix3d &covariance_matrix)
	Compute the normalized 3x3 covariance matrix for a already demeaned point cloud.
template<typename PointT >
unsigned int	computeCovarianceMatrix (const pcl::PointCloud< PointT > &cloud, const pcl::PointIndices &indices, Eigen::Matrix3d &covariance_matrix)
	Compute the normalized 3x3 covariance matrix for a already demeaned point cloud.
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	demeanPointCloud (const pcl::PointCloud< PointT > &cloud_in, const pcl::PointIndices &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 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 Scalar >
Scalar	sqrt (const Scalar &val)
template<>
double	sqrt< double > (const double &val)
template<>
float	sqrt< float > (const float &val)
template<>
long double	sqrt< long double > (const long double &val)
template<typename Scalar , typename Roots >
void	computeRoots2 (const Scalar &b, const Scalar &c, Roots &roots)
	Compute the roots of a quadratic polynom x^2 + b*x + c = 0.
template<typename Matrix , typename Roots >
void	computeRoots (const Matrix &m, Roots &roots)
	computes the roots of the characteristic polynomial of the input matrix m, which are the eigenvalues
template<typename Matrix , typename Vector >
void	eigen22 (const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
	determine the smallest eigenvalue and its corresponding eigenvector
template<typename Matrix , typename Vector >
void	eigen22 (const Matrix &mat, Matrix &eigenvectors, Vector &eigenvalues)
	determine the smallest eigenvalue and its corresponding eigenvector
template<typename Matrix , typename Vector >
void	computeCorrespondingEigenVector (const Matrix &mat, const typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
	determines the corresponding eigenvector to the given eigenvalue of the symmetric positive semi definite input matrix
template<typename Matrix , typename Vector >
void	eigen33 (const Matrix &mat, typename Matrix::Scalar &eigenvalue, Vector &eigenvector)
	determines the eigenvector and eigenvalue of the smallest eigenvalue of the symmetric positive semi definite input matrix
template<typename Matrix , typename Vector >
void	eigen33 (const Matrix &mat, Vector &evals)
	determines the eigenvalues of the symmetric positive semi definite input matrix
template<typename Matrix , typename Vector >
void	eigen33 (const Matrix &mat, Matrix &evecs, Vector &evals)
	determines the eigenvalues and corresponding eigenvectors of the symmetric positive semi definite input matrix
template<typename Matrix >
Matrix::Scalar	invert2x2 (const Matrix &matrix, Matrix &inverse)
	Calculate the inverse of a 2x2 matrix.
template<typename Matrix >
Matrix::Scalar	invert3x3SymMatrix (const Matrix &matrix, Matrix &inverse)
	Calculate the inverse of a 3x3 symmetric matrix.
template<typename Matrix >
Matrix::Scalar	invert3x3Matrix (const Matrix &matrix, Matrix &inverse)
	Calculate the inverse of a general 3x3 matrix.
template<typename Matrix >
Matrix::Scalar	determinant3x3Matrix (const Matrix &matrix)
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)
	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	getTransformationFromTwoUnitVectors (const Eigen::Vector3f &y_direction, const Eigen::Vector3f &z_axis)
	Get the unique 3D rotation that will rotate z_axis into (0,0,1) and y_direction into a vector with x=0 (or into (0,1,0) should y_direction be orthogonal to z_axis)
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 > const &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.
PCL_EXPORTS bool	planeWithPlaneIntersection (const Eigen::Vector4f &plane_a, const Eigen::Vector4f &fplane_b, Eigen::VectorXf &line, double angular_tolerance=0.1)
	Determine the line of intersection of two non-parallel planes using lagrange multipliers in: "Intersection of Two Planes, John Krumm, Microsoft Research, Redmond, WA, USA".
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 >
int	getFieldIndex (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 >
void	getFields (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.
PCL_EXPORTS void	copyPointCloud (const sensor_msgs::PointCloud2 &cloud_in, sensor_msgs::PointCloud2 &cloud_out)
	Copy fields and point cloud data from cloud_in to cloud_out.
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.
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
void	getRejectedQueryIndices (const pcl::Correspondences &correspondences_before, const pcl::Correspondences &correspondences_after, std::vector< int > &indices, bool presorting_required=true)
	Get the query points of correspondences that are present in one correspondence vector but not in the other, e.g., to compare correspondences before and after rejection.
bool	isBetterCorrespondence (const Correspondence &pc1, const Correspondence &pc2)
	Comparator to enable us to sort a vector of PointCorrespondences according to their scores using std::sort (begin(), end(), isBetterCorrespondence);.
template<typename Sequence , typename F >
void	for_each_type (F f)
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 PointXYZL &p)
std::ostream &	operator<< (std::ostream &os, const Label &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 PointXYZRGBL &p)
std::ostream &	operator<< (std::ostream &os, const PointXYZHSV &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 Axis &p)
std::ostream &	operator<< (std::ostream &os, const _Axis &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 PFHRGBSignature250 &p)
std::ostream &	operator<< (std::ostream &os, const PPFSignature &p)
std::ostream &	operator<< (std::ostream &os, const PPFRGBSignature &p)
std::ostream &	operator<< (std::ostream &os, const NormalBasedSignature12 &p)
std::ostream &	operator<< (std::ostream &os, const ShapeContext &p)
	PCL_DEPRECATED (inline std::ostream &operator<< (std::ostream &os, const SHOT &p),"SHOT POINT IS DEPRECATED, USE SHOT352 FOR SHAPE AND SHOT1344 FOR SHAPE+COLOR INSTEAD")
std::ostream &	operator<< (std::ostream &os, const SHOT &p)
std::ostream &	operator<< (std::ostream &os, const SHOT352 &p)
std::ostream &	operator<< (std::ostream &os, const SHOT1344 &p)
std::ostream &	operator<< (std::ostream &os, const ReferenceFrame &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 ESFSignature640 &p)
std::ostream &	operator<< (std::ostream &os, const GFPFHSignature16 &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 PointT >
bool	isFinite (const PointT &pt)
	Tests if the 3D components of a point are all finite param[in] pt point to be tested.
template<>
bool	isFinite< pcl::Normal > (const pcl::Normal &n)
std::ostream &	operator<< (std::ostream &s, const ::pcl::ModelCoefficients &v)
template<typename PointT >
std::ostream &	operator<< (std::ostream &s, const pcl::PointCloud< PointT > &p)
virtual void	copyToFloatArray (const SHOT &p, float *out) const
struct	PCL_DEPRECATED_CLASS (SHOT,"USE SHOT352 FOR SHAPE AND SHOT1344 FOR SHAPE+COLOR INSTEAD")
	Members: std::vector<float> descriptor, rf[9].
void	PointXYZRGBtoXYZI (PointXYZRGB &in, PointXYZI &out)
	Convert a XYZRGB point type to a XYZI.
void	PointXYZRGBtoXYZHSV (PointXYZRGB &in, PointXYZHSV &out)
	Convert a XYZRGB point type to a XYZHSV.
void	PointXYZHSVtoXYZRGB (PointXYZHSV &in, PointXYZRGB &out)
	Convert a XYZHSV point type to a XYZRGB.
void	PointCloudXYZRGBtoXYZHSV (PointCloud< PointXYZRGB > &in, PointCloud< PointXYZHSV > &out)
	Convert a XYZRGB point cloud to a XYZHSV.
void	PointCloudXYZRGBtoXYZI (PointCloud< PointXYZRGB > &in, PointCloud< PointXYZI > &out)
	Convert a XYZRGB point cloud to a XYZI.
std::ostream &	operator<< (std::ostream &s, const ::pcl::PointIndices &v)
std::ostream &	operator<< (std::ostream &s, const ::pcl::PolygonMesh &v)
std::ostream &	operator<< (std::ostream &os, const RangeImage &r)
	/ingroup range_image
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)
	Convert a PointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.
template<typename PointT >
void	fromROSMsg (const sensor_msgs::PointCloud2 &msg, pcl::PointCloud< PointT > &cloud)
	Convert a PointCloud2 binary data blob into a pcl::PointCloud<T> object.
template<typename PointT >
void	toROSMsg (const pcl::PointCloud< PointT > &cloud, sensor_msgs::PointCloud2 &msg)
	Convert a pcl::PointCloud<T> object to a PointCloud2 binary data blob.
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.
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 , typename Scalar >
void	flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Matrix< Scalar, 4, 1 > &normal)
	Flip (in place) the estimated normal of a point towards a given viewpoint.
template<typename PointT , typename Scalar >
void	flipNormalTowardsViewpoint (const PointT &point, float vp_x, float vp_y, float vp_z, Eigen::Matrix< Scalar, 3, 1 > &normal)
	Flip (in place) the estimated normal of a point towards a given viewpoint.
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	computeRGBPairFeatures (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4i &colors1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, const Eigen::Vector4i &colors2, float &f1, float &f2, float &f3, float &f4, float &f5, float &f6, float &f7)
PCL_EXPORTS bool	computePPFPairFeature (const Eigen::Vector4f &p1, const Eigen::Vector4f &n1, const Eigen::Vector4f &p2, const Eigen::Vector4f &n2, float &f1, float &f2, float &f3, float &f4)
template<int N>
void	getFeaturePointCloud (const std::vector< Eigen::MatrixXf, Eigen::aligned_allocator< Eigen::MatrixXf > > &histograms2D, PointCloud< Histogram< N > > &histogramsPC)
	Transform a list of 2D matrices into a point cloud containing the values in a vector (Histogram<N>).
template<typename PointInT , typename PointNT , typename PointOutT >
Eigen::MatrixXf	computeRSD (boost::shared_ptr< const pcl::PointCloud< PointInT > > &surface, boost::shared_ptr< const pcl::PointCloud< PointNT > > &normals, const std::vector< int > &indices, double max_dist, int nr_subdiv, double plane_radius, PointOutT &radii, bool compute_histogram=false)
	Estimate the Radius-based Surface Descriptor (RSD) for a given point based on its spatial neighborhood of 3D points with normals.
template<typename PointNT , typename PointOutT >
Eigen::MatrixXf	computeRSD (boost::shared_ptr< const pcl::PointCloud< PointNT > > &normals, const std::vector< int > &indices, const std::vector< float > &sqr_dists, double max_dist, int nr_subdiv, double plane_radius, PointOutT &radii, bool compute_histogram=false)
	Estimate the Radius-based Surface Descriptor (RSD) for a given point based on its spatial neighborhood of 3D points with normals.
template<typename PointInT , typename PointNT , typename PointRFT >
class	PCL_DEPRECATED_CLASS (SHOTEstimation,"SHOTEstimation<..., pcl::SHOT, ...> IS DEPRECATED, USE SHOTEstimation<..., pcl::SHOT352, ...> INSTEAD")< PointInT
	SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals.
template<typename PointNT , typename PointRFT >
class	PCL_DEPRECATED_CLASS (SHOTEstimation,"SHOTEstimation<pcl::PointXYZRGBA,...,pcl::SHOT,...> IS DEPRECATED, USE SHOTEstimation<pcl::PointXYZRGBA,...,pcl::SHOT352,...> FOR SHAPE AND SHOTColorEstimation<pcl::PointXYZRGBA,...,pcl::SHOT1344,...> FOR SHAPE+COLOR INSTEAD")< pcl
	SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals.
template<typename PointNT , typename PointRFT >
class	PCL_DEPRECATED_CLASS (SHOTEstimation,"SHOTEstimation<pcl::PointXYZRGBA,...,Eigen::MatrixXf,...> IS DEPRECATED, USE SHOTColorEstimation<pcl::PointXYZRGBA,...,Eigen::MatrixXf,...> FOR SHAPE AND SHAPE+COLOR INSTEAD")< pcl
	SHOTEstimation estimates the Signature of Histograms of OrienTations (SHOT) descriptor for a given point cloud dataset containing points and normals.
template<typename PointInT , typename PointNT , typename PointRFT >
class	PCL_DEPRECATED_CLASS (SHOTEstimationOMP,"SHOTEstimationOMP<..., pcl::SHOT, ...> IS DEPRECATED, USE SHOTEstimationOMP<..., pcl::SHOT352, ...> INSTEAD")< PointInT
template<typename PointNT , typename PointRFT >
class	PCL_DEPRECATED_CLASS (SHOTEstimationOMP,"SHOTEstimationOMP<pcl::PointXYZRGBA,...,pcl::SHOT,...> IS DEPRECATED, USE SHOTEstimationOMP<pcl::PointXYZRGBA,...,pcl::SHOT352,...> FOR SHAPE AND SHOTColorEstimationOMP<pcl::PointXYZRGBA,...,pcl::SHOT1344,...> FOR SHAPE+COLOR INSTEAD")< pcl
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.
template<typename PointT >
void	removeNaNFromPointCloud (const pcl::PointCloud< PointT > &cloud_in, std::vector< int > &index)
	Removes points with x, y, or z equal to NaN.
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)
	Obtain the maximum and minimum points in 3D from a given point cloud.
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)
	Obtain the maximum and minimum points in 3D from a given point cloud.
Eigen::MatrixXi	getHalfNeighborCellIndices ()
	Get the relative cell indices of the "upper half" 13 neighbors.
Eigen::MatrixXi	getAllNeighborCellIndices ()
	Get the relative cell indices of all the 26 neighbors.
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 PointT >
void	approximatePolygon (const PlanarPolygon< PointT > &polygon, PlanarPolygon< PointT > &approx_polygon, float threshold, bool refine=false, bool closed=true)
	see approximatePolygon2D
template<typename PointT >
void	approximatePolygon2D (const typename PointCloud< PointT >::VectorType &polygon, typename PointCloud< PointT >::VectorType &approx_polygon, float threshold, bool refine=false, bool closed=true)
	returns an approximate polygon to given 2D contour.
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)
template<typename Type >
bool	isValueFinite (const sensor_msgs::PointCloud2 &cloud, const unsigned int point_index, const int point_size, const unsigned int field_idx, const unsigned int fields_count)
	Check whether a given value of type Type (uchar, char, uint, int, float, double, ...) is finite or not.
template<typename Type >
void	copyStringValue (const std::string &st, sensor_msgs::PointCloud2 &cloud, unsigned int point_index, unsigned int field_idx, unsigned int fields_count)
	Copy one single value of type T (uchar, char, uint, int, float, double, ...) from a string.
template<>
void	copyStringValue< int8_t > (const std::string &st, sensor_msgs::PointCloud2 &cloud, unsigned int point_index, unsigned int field_idx, unsigned int fields_count)
template<>
void	copyStringValue< uint8_t > (const std::string &st, sensor_msgs::PointCloud2 &cloud, unsigned int point_index, unsigned int field_idx, unsigned int fields_count)
PCL_EXPORTS unsigned int	lzfCompress (const void *const in_data, unsigned int in_len, void *out_data, unsigned int out_len)
	Compress in_len bytes stored at the memory block starting at in_data and write the result to out_data, up to a maximum length of out_len bytes using Marc Lehmann's LZF algorithm.
PCL_EXPORTS unsigned int	lzfDecompress (const void *const in_data, unsigned int in_len, void *out_data, unsigned int out_len)
	Decompress data compressed with the lzfCompress function and stored at location in_data and length in_len.
void	throwPCLIOException (const char *function_name, const char *file_name, unsigned line_number, const char *format,...)
template<typename PointT >
void	getApproximateIndices (const typename pcl::PointCloud< PointT >::Ptr &cloud_in, const typename pcl::PointCloud< PointT >::Ptr &cloud_ref, std::vector< int > &indices)
	Get a set of approximate indices for a given point cloud into a reference point cloud.
template<typename Point1T , typename Point2T >
void	getApproximateIndices (const typename pcl::PointCloud< Point1T >::Ptr &cloud_in, const typename pcl::PointCloud< Point2T >::Ptr &cloud_ref, std::vector< int > &indices)
	Get a set of approximate indices for a given point cloud into a reference point cloud.
std::ostream &	operator<< (std::ostream &os, const NarfKeypoint::Parameters &p)
template<typename Point >
void	projectPoint (const Point &p, const Eigen::Vector4f &model_coefficients, Point &q)
	Project a point on a planar model given by a set of normalized coefficients.
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< search::Search< PointT > > &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
	Decompose a region of space into clusters based on the Euclidean distance between points.
template<typename PointT >
void	extractEuclideanClusters (const PointCloud< PointT > &cloud, const std::vector< int > &indices, const boost::shared_ptr< search::Search< PointT > > &tree, float tolerance, std::vector< PointIndices > &clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)())
	Decompose a region of space into clusters based on the Euclidean distance between points.
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 >
void	extractLabeledEuclideanClusters (const PointCloud< PointT > &cloud, const boost::shared_ptr< search::Search< PointT > > &tree, float tolerance, std::vector< std::vector< PointIndices > > &labeled_clusters, unsigned int min_pts_per_cluster=1, unsigned int max_pts_per_cluster=(std::numeric_limits< int >::max)(), unsigned int max_label=(std::numeric_limits< int >::max))
	Decompose a region of space into clusters based on the Euclidean distance between points.
bool	compareLabeledPointClusters (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::search::Search< PointT > > &tree, pcl::PointCloud< PointT > &output)
	Obtain the difference between two aligned point clouds as another point cloud, given a distance threshold.
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
struct pcl::_PointXYZHSV	EIGEN_ALIGN16
class< SHOT >	__pad0__
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]

---

Typedef Documentation

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

Definition at line 174 of file point_types.hpp.

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

Definition at line 175 of file point_types.hpp.

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

Definition at line 176 of file point_types.hpp.

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

Definition at line 177 of file point_types.hpp.

typedef BivariatePolynomialT<float> pcl::BivariatePolynomial

Definition at line 137 of file bivariate_polynomial.h.

typedef BivariatePolynomialT<double> pcl::BivariatePolynomiald

Definition at line 136 of file bivariate_polynomial.h.

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

Definition at line 92 of file correspondence.h.

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

Definition at line 94 of file correspondence.h.

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

Definition at line 93 of file correspondence.h.

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 69 of file point_cloud.h.

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

Definition at line 133 of file correspondence.h.

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

Definition at line 149 of file correspondence.h.

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

Definition at line 27 of file PointIndices.h.

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

Definition at line 26 of file PointIndices.h.

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

Definition at line 33 of file PolygonMesh.h.

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

Definition at line 32 of file PolygonMesh.h.

typedef PolynomialCalculationsT<float> pcl::PolynomialCalculations

Definition at line 129 of file polynomial_calculations.h.

typedef PolynomialCalculationsT<double> pcl::PolynomialCalculationsd

Definition at line 128 of file polynomial_calculations.h.

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

Definition at line 112 of file TextureMesh.h.

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

Definition at line 111 of file TextureMesh.h.

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

Definition at line 178 of file point_types.hpp.

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

Definition at line 179 of file point_types.hpp.

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

Definition at line 180 of file point_types.hpp.

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

Definition at line 181 of file point_types.hpp.

typedef VectorAverage<float, 2> pcl::VectorAverage2f

Definition at line 110 of file vector_average.h.

typedef VectorAverage<float, 3> pcl::VectorAverage3f

Definition at line 111 of file vector_average.h.

typedef VectorAverage<float, 4> pcl::VectorAverage4f

Definition at line 112 of file vector_average.h.

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

Definition at line 27 of file Vertices.h.

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

Definition at line 26 of file Vertices.h.

---

Enumeration Type Documentation

enum pcl::SacModel

Enumerator:

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

Definition at line 45 of file model_types.h.

---

Function Documentation

template<typename PointT >

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

see approximatePolygon2D

Author:

Suat Gedikli <gedikli@willowgarage.com>

Definition at line 43 of file polygon_operations.hpp.

template<typename PointT >

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

returns an approximate polygon to given 2D contour.

Uses just X and Y values.

Note:

if refinement is not turned on, the resulting polygon will contain points from the original contour with their original z values (if any)

if refinement is turned on, the z values of the refined polygon are not valid and should be set to 0 if point contains z attribute.

Parameters:

[in]	polygon	input polygon
[out]	approx_polygon	approximate polygon
[in]	threshold	maximum allowed distance of an input vertex to an output edge
[in]	closed	whether it is a closed polygon or a polyline

Author:

Suat Gedikli <gedikli@willowgarage.com>

Definition at line 71 of file polygon_operations.hpp.

PCL_EXPORTS bool pcl::computePPFPairFeature	(	const Eigen::Vector4f &	p1,
		const Eigen::Vector4f &	n1,
		const Eigen::Vector4f &	p2,
		const Eigen::Vector4f &	n2,
		float &	f1,
		float &	f2,
		float &	f3,
		float &	f4
	)

Parameters:

[in]	p1
[in]	n1
[in]	p2
[in]	n2
[out]	f1
[out]	f2
[out]	f3
[out]	f4

PCL_EXPORTS bool pcl::computeRGBPairFeatures	(	const Eigen::Vector4f &	p1,
		const Eigen::Vector4f &	n1,
		const Eigen::Vector4i &	colors1,
		const Eigen::Vector4f &	p2,
		const Eigen::Vector4f &	n2,
		const Eigen::Vector4i &	colors2,
		float &	f1,
		float &	f2,
		float &	f3,
		float &	f4,
		float &	f5,
		float &	f6,
		float &	f7
	)

template<typename Matrix , typename Roots >

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

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

Parameters:

[in]	m	input matrix
[out]	roots	roots of the characteristic polynomial of the input matrix m, which are the eigenvalues

Definition at line 142 of file eigen.h.

template<typename Scalar , typename Roots >

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

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

Parameters:

[in]	b	linear parameter
[in]	c	constant parameter
[out]	roots	solutions of x^2 + b*x + c = 0

Definition at line 124 of file eigen.h.

template<typename Type >

void pcl::copyStringValue	(	const std::string &	st,
		sensor_msgs::PointCloud2 &	cloud,
		unsigned int	point_index,
		unsigned int	field_idx,
		unsigned int	fields_count
	)		[inline]

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

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

Parameters:

[in]	st	the string containing the value to convert and copy
[out]	cloud	the cloud to copy it to
[in]	point_index	the index of the point
[in]	field_idx	the index of the dimension/field
[in]	fields_count	the current fields count

Definition at line 317 of file file_io.h.

template<>

void pcl::copyStringValue< int8_t >	(	const std::string &	st,
		sensor_msgs::PointCloud2 &	cloud,
		unsigned int	point_index,
		unsigned int	field_idx,
		unsigned int	fields_count
	)		[inline]

Definition at line 339 of file file_io.h.

template<>

void pcl::copyStringValue< uint8_t >	(	const std::string &	st,
		sensor_msgs::PointCloud2 &	cloud,
		unsigned int	point_index,
		unsigned int	field_idx,
		unsigned int	fields_count
	)		[inline]

Definition at line 363 of file file_io.h.

virtual void pcl::copyToFloatArray	(	const SHOT &	p,
		float *	out
	)		const [virtual]

Definition at line 455 of file point_representation.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 234 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]

Definition at line 249 of file file_io.h.

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]

Definition at line 265 of file file_io.h.

template<typename PointT >

void pcl::createMapping	(	const std::vector< sensor_msgs::PointField > &	msg_fields,
		MsgFieldMap &	field_map
	)

Definition at line 119 of file conversions.h.

template<typename Matrix >

Matrix::Scalar pcl::determinant3x3Matrix

(

const Matrix &

matrix

)

[inline]

Definition at line 700 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.

Parameters:

[in]	p1	the first point
[in]	p2	the second point

Definition at line 184 of file distances.h.

template<typename Sequence , typename F >

void pcl::for_each_type

(

F

f

)

[inline]

Definition at line 91 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
	)

Convert a PointCloud2 binary data blob into a pcl::PointCloud<T> object using a field_map.

Parameters:

[in]	msg	the PointCloud2 binary blob
[out]	cloud	the resultant pcl::PointCloud<T>
[in]	field_map	a MsgFieldMap object

Note:

Use fromROSMsg (PointCloud2, PointCloud<T>) directly or create you own MsgFieldMap using:

 MsgFieldMap field_map;
 createMapping<PointT> (msg.fields, field_map);

Definition at line 163 of file conversions.h.

template<typename PointT >

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

Convert a PointCloud2 binary data blob into a pcl::PointCloud<T> object.

Parameters:

[in]	msg	the PointCloud2 binary blob
[out]	cloud	the resultant pcl::PointCloud<T>

Definition at line 221 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.

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
	)

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

Parameters:

[in]	cloud	the pointer to a sensor_msgs::PointCloud2 dataset
[in]	x_idx	the index of the X channel
[in]	y_idx	the index of the Y channel
[in]	z_idx	the index of the Z channel
[out]	min_pt	the minimum data point
[out]	max_pt	the maximum data point

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
	)

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

Note:

Performs internal data filtering as well.

Parameters:

[in]	cloud	the pointer to a sensor_msgs::PointCloud2 dataset
[in]	x_idx	the index of the X channel
[in]	y_idx	the index of the Y channel
[in]	z_idx	the index of the Z channel
[in]	distance_field_name	the name of the dimension to filter data along to
[in]	min_distance	the minimum acceptable value in distance_field_name data
[in]	max_distance	the maximum acceptable value in distance_field_name data
[out]	min_pt	the minimum data point
[out]	max_pt	the maximum data point
[in]	limit_negative	false if data inside of the [min_distance; max_distance] interval should be considered, true otherwise.

void pcl::getRejectedQueryIndices	(	const pcl::Correspondences &	correspondences_before,
		const pcl::Correspondences &	correspondences_after,
		std::vector< int > &	indices,
		bool	presorting_required = true
	)

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

Parameters:

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

double pcl::getTime

(

)

[inline]

Definition at line 142 of file time.h.

template<typename PointT >

bool pcl::isFinite

(

const PointT &

pt

)

[inline]

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

Definition at line 1309 of file point_types.hpp.

template<>

bool pcl::isFinite< pcl::Normal >

(

const pcl::Normal &

n

)

[inline]

Definition at line 1316 of file point_types.hpp.

template<typename Type >

bool pcl::isValueFinite	(	const sensor_msgs::PointCloud2 &	cloud,
		const unsigned int	point_index,
		const int	point_size,
		const unsigned int	field_idx,
		const unsigned int	fields_count
	)		[inline]

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

Parameters:

[in]	cloud	the cloud that contains the data
[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

Returns:

true if the value is finite, false otherwise

Definition at line 292 of file file_io.h.

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

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

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

Note:

The buffers must not be overlapping.

Parameters:

[in]	in_data	the input uncompressed buffer
[in]	in_len	the length of the input buffer
[out]	out_data	the output buffer where the compressed result will be stored
[out]	out_len	the length of the output buffer

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

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

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

If the output buffer is not large enough to hold the decompressed data, a 0 is returned and errno is set to E2BIG. Otherwise the number of decompressed bytes (i.e. the original length of the data) is returned.

If an error in the compressed data is detected, a zero is returned and errno is set to EINVAL.

This function is very fast, about as fast as a copying loop.

Parameters:

[in]	in_data	the input compressed buffer
[in]	in_len	the length of the input buffer
[out]	out_data	the output buffer (must be resized to out_len)
[out]	out_len	the length of the output buffer

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

Definition at line 29 of file Vertices.h.

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 &	s,
		const ::pcl::ModelCoefficients &	v
	)		[inline]

Definition at line 30 of file ModelCoefficients.h.

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 RangeImageBorderExtractor::Parameters &	p
	)		[inline]

Definition at line 57 of file range_image_border_extractor.hpp.

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

overloaded << operator

Definition at line 86 of file correspondence.h.

template<typename real >

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

Definition at line 230 of file bivariate_polynomial.hpp.

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

Definition at line 212 of file point_types.hpp.

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

Definition at line 277 of file point_types.hpp.

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

Definition at line 301 of file point_types.hpp.

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

Definition at line 312 of file point_types.hpp.

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

Definition at line 361 of file point_types.hpp.

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

Definition at line 444 of file point_types.hpp.

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

Definition at line 473 of file point_types.hpp.

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

Definition at line 512 of file point_types.hpp.

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

Definition at line 527 of file point_types.hpp.

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

Definition at line 549 of file point_types.hpp.

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

Definition at line 588 of file point_types.hpp.

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

Definition at line 619 of file point_types.hpp.

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

Definition at line 625 of file point_types.hpp.

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

Definition at line 659 of file point_types.hpp.

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

Definition at line 736 of file point_types.hpp.

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

Definition at line 772 of file point_types.hpp.

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

Definition at line 805 of file point_types.hpp.

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

/ingroup range_image

Definition at line 813 of file range_image.h.

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

Definition at line 839 of file point_types.hpp.

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

Definition at line 852 of file point_types.hpp.

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

Definition at line 865 of file point_types.hpp.

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

Definition at line 878 of file point_types.hpp.

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

Definition at line 902 of file point_types.hpp.

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

Definition at line 915 of file point_types.hpp.

std::ostream& pcl::operator<<	(	std::ostream &	os,
		const PFHRGBSignature250 &	p
	)		[inline]

Definition at line 929 of file point_types.hpp.

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

Definition at line 944 of file point_types.hpp.

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

Definition at line 959 of file point_types.hpp.

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

Definition at line 974 of file point_types.hpp.

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

Definition at line 990 of file point_types.hpp.

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

Definition at line 1009 of file point_types.hpp.

std::ostream& pcl::operator<<	(	std::ostream &	os,
		const SHOT352 &	p
	)		[inline]

Definition at line 1027 of file point_types.hpp.

template<typename PointT >

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

Definition at line 1034 of file point_cloud.h.

std::ostream& pcl::operator<<	(	std::ostream &	os,
		const SHOT1344 &	p
	)		[inline]

Definition at line 1045 of file point_types.hpp.

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

Definition at line 1100 of file point_types.hpp.

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

Definition at line 1113 of file point_types.hpp.

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

Definition at line 1127 of file point_types.hpp.

std::ostream& pcl::operator<<	(	std::ostream &	os,
		const ESFSignature640 &	p
	)		[inline]

Definition at line 1141 of file point_types.hpp.

std::ostream& pcl::operator<<	(	std::ostream &	os,
		const GFPFHSignature16 &	p
	)		[inline]

Definition at line 1156 of file point_types.hpp.

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

Definition at line 1171 of file point_types.hpp.

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

Definition at line 1189 of file point_types.hpp.

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

Definition at line 1211 of file point_types.hpp.

template<int N>

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

Definition at line 1226 of file point_types.hpp.

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

Definition at line 1252 of file point_types.hpp.

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

Definition at line 1291 of file point_types.hpp.

pcl::PCL_DEPRECATED	(	inline std::ostream &operator<<	std::ostream &os, const SHOT &p,
		"SHOT POINT IS	DEPRECATED,
		USE SHOT352 FOR SHAPE AND SHOT1344 FOR SHAPE+COLOR INSTEAD"
	)

template<typename PointInT , typename PointNT , typename PointRFT >

class pcl::PCL_DEPRECATED_CLASS	(	SHOTEstimationOMP	,
		"SHOTEstimationOMP<..., pcl::SHOT, ...> IS	DEPRECATED,
		USE SHOTEstimationOMP<..., pcl::SHOT352,...> INSTEAD"
	)

template<typename PointNT , typename PointRFT >

class pcl::PCL_DEPRECATED_CLASS	(	SHOTEstimationOMP	,
		"SHOTEstimationOMP<pcl::PointXYZRGBA,...,pcl::SHOT,...> IS	DEPRECATED,
		USE SHOTEstimationOMP< pcl::PointXYZRGBA,..., pcl::SHOT352,...> FOR SHAPE AND SHOTColorEstimationOMP< pcl::PointXYZRGBA,..., pcl::SHOT1344,...> FOR SHAPE+COLOR INSTEAD"
	)

Empty constructor.

Initialize the scheduler and set the number of threads to use.

Parameters:

nr_threads

the number of hardware threads to use (-1 sets the value back to automatic)

Estimate the Signatures of Histograms of OrienTations (SHOT) descriptors at a set of points given by <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()

Parameters:

output

the resultant point cloud model dataset that contains the SHOT feature estimates

The number of threads the scheduler should use.

Definition at line 257 of file shot_omp.h.

PCL_EXPORTS bool pcl::planeWithPlaneIntersection	(	const Eigen::Vector4f &	plane_a,
		const Eigen::Vector4f &	fplane_b,
		Eigen::VectorXf &	line,
		double	angular_tolerance = 0.1
	)

Determine the line of intersection of two non-parallel planes using lagrange multipliers in: "Intersection of Two Planes, John Krumm, Microsoft Research, Redmond, WA, USA".

Parameters:

[in]	coefficients	of plane A and plane B in the form ax + by + cz + d = 0
[out]	coefficients	of line where line.tail<3>() = direction vector and line.head<3>() the point on the line clossest to (0, 0, 0)

Returns:

true if succeeded/planes aren't parallel

void pcl::PointCloudXYZRGBtoXYZHSV	(	PointCloud< PointXYZRGB > &	in,
		PointCloud< PointXYZHSV > &	out
	)		[inline]

Convert a XYZRGB point cloud to a XYZHSV.

Parameters:

[in]	in	the input XYZRGB point cloud
[out]	out	the output XYZHSV point cloud

Definition at line 171 of file point_types_conversion.h.

void pcl::PointCloudXYZRGBtoXYZI	(	PointCloud< PointXYZRGB > &	in,
		PointCloud< PointXYZI > &	out
	)		[inline]

Convert a XYZRGB point cloud to a XYZI.

Parameters:

[in]	in	the input XYZRGB point cloud
[out]	out	the output XYZI point cloud

Definition at line 188 of file point_types_conversion.h.

void pcl::PointXYZHSVtoXYZRGB	(	PointXYZHSV &	in,
		PointXYZRGB &	out
	)		[inline]

Convert a XYZHSV point type to a XYZRGB.

Parameters:

[in]	in	the input XYZHSV point
[out]	out	the output XYZRGB point

Definition at line 103 of file point_types_conversion.h.

void pcl::PointXYZRGBtoXYZHSV	(	PointXYZRGB &	in,
		PointXYZHSV &	out
	)		[inline]

Convert a XYZRGB point type to a XYZHSV.

Parameters:

[in]	in	the input XYZRGB point
[out]	out	the output XYZHSV point

Definition at line 67 of file point_types_conversion.h.

void pcl::PointXYZRGBtoXYZI	(	PointXYZRGB &	in,
		PointXYZI &	out
	)		[inline]

Convert a XYZRGB point type to a XYZI.

Parameters:

[in]	in	the input XYZRGB point
[out]	out	the output XYZI point

Definition at line 54 of file point_types_conversion.h.

template<typename Point >

void pcl::projectPoint	(	const Point &	p,
		const Eigen::Vector4f &	model_coefficients,
		Point &	q
	)		[inline]

Project a point on a planar model given by a set of normalized coefficients.

Parameters:

[in]	p	the input point to project
[in]	model_coefficients	the coefficients of the plane (a, b, c, d) that satisfy ax+by+cz+d=0
[out]	q	the resultant projected point

Definition at line 55 of file sac_model_plane.h.

template<typename Scalar >

Scalar pcl::sqrt

(

const Scalar &

val

)

[inline]

Definition at line 96 of file eigen.h.

template<>

double pcl::sqrt< double >

(

const double &

val

)

[inline]

Definition at line 101 of file eigen.h.

template<>

float pcl::sqrt< float >

(

const float &

val

)

[inline]

Definition at line 107 of file eigen.h.

template<>

long double pcl::sqrt< long double >

(

const long double &

val

)

[inline]

Definition at line 113 of file eigen.h.

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.

Parameters:

[in]	p1	the first point
[in]	p2	the second point

Definition at line 174 of file distances.h.

template<typename PointT >

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

Convert a pcl::PointCloud<T> object to a PointCloud2 binary data blob.

Parameters:

[in]	cloud	the input pcl::PointCloud<T>
[out]	msg	the resultant PointCloud2 binary blob

Definition at line 233 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:

[in]	cloud	the point cloud message
[out]	msg	the resultant sensor_msgs::Image CloudT cloud type, CloudT should be akin to pcl::PointCloud<pcl::PointXYZRGBA>

Note:

will throw std::runtime_error if there is a problem

Definition at line 271 of file conversions.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 304 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:

Can be used with cloud_in equal to cloud_out

Definition at line 120 of file transforms.hpp.

---

Variable Documentation

class<SHOT> pcl::__pad0__

Definition at line 451 of file point_representation.h.

const unsigned int pcl::edgeTable[256]

Definition at line 59 of file marching_cubes.h.

struct pcl::_PointXYZHSV pcl::EIGEN_ALIGN16

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.