Point Cloud Library (PCL): pcl::PointCloud< PointT

PointCloud represents the base class in PCL for storing collections of 3D points. More...

#include <pcl/common/distances.h>

Public Types
using	PointType = PointT

using	VectorType = std::vector< PointT, Eigen::aligned_allocator< PointT > >

using	CloudVectorType = std::vector< PointCloud< PointT >, Eigen::aligned_allocator< PointCloud< PointT > > >

using	Ptr = shared_ptr< PointCloud< PointT > >

using	ConstPtr = shared_ptr< const PointCloud< PointT > >

using	value_type = PointT

using	reference = PointT &

using	const_reference = const PointT &

using	difference_type = typename VectorType::difference_type

using	size_type = typename VectorType::size_type

using	iterator = typename VectorType::iterator

using	const_iterator = typename VectorType::const_iterator

using	reverse_iterator = typename VectorType::reverse_iterator

using	const_reverse_iterator = typename VectorType::const_reverse_iterator

Public Member Functions
	PointCloud ()=default
	Default constructor. More...

	PointCloud (const PointCloud< PointT > &pc, const Indices &indices)
	Copy constructor from point cloud subset. More...

	PointCloud (std::uint32_t width_, std::uint32_t height_, const PointT &value_=PointT())
	Allocate constructor from point cloud subset. More...

PointCloud &	operator+= (const PointCloud &rhs)
	Add a point cloud to the current cloud. More...

PointCloud	operator+ (const PointCloud &rhs)
	Add a point cloud to another cloud. More...

const PointT &	at (int column, int row) const
	Obtain the point given by the (column, row) coordinates. More...

PointT &	at (int column, int row)
	Obtain the point given by the (column, row) coordinates. More...

const PointT &	operator() (std::size_t column, std::size_t row) const
	Obtain the point given by the (column, row) coordinates. More...

PointT &	operator() (std::size_t column, std::size_t row)
	Obtain the point given by the (column, row) coordinates. More...

bool	isOrganized () const
	Return whether a dataset is organized (e.g., arranged in a structured grid). More...

Eigen::Map< Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> >	getMatrixXfMap (int dim, int stride, int offset)
	Return an Eigen MatrixXf (assumes float values) mapped to the specified dimensions of the PointCloud. More...

const Eigen::Map< const Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> >	getMatrixXfMap (int dim, int stride, int offset) const
	Return an Eigen MatrixXf (assumes float values) mapped to the specified dimensions of the PointCloud. More...

Eigen::Map< Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> >	getMatrixXfMap ()

const Eigen::Map< const Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> >	getMatrixXfMap () const

iterator	begin () noexcept

iterator	end () noexcept

const_iterator	begin () const noexcept

const_iterator	end () const noexcept

const_iterator	cbegin () const noexcept

const_iterator	cend () const noexcept

reverse_iterator	rbegin () noexcept

reverse_iterator	rend () noexcept

const_reverse_iterator	rbegin () const noexcept

const_reverse_iterator	rend () const noexcept

const_reverse_iterator	crbegin () const noexcept

const_reverse_iterator	crend () const noexcept

std::size_t	size () const

index_t	max_size () const noexcept

void	reserve (std::size_t n)

bool	empty () const

PointT *	data () noexcept

const PointT *	data () const noexcept

void	resize (std::size_t count)
	Resizes the container to contain `count` elements. More...

void	resize (index_t count, const PointT &value)
	Resizes the container to contain count elements. More...

const PointT &	operator[] (std::size_t n) const

PointT &	operator[] (std::size_t n)

const PointT &	at (std::size_t n) const

PointT &	at (std::size_t n)

const PointT &	front () const

PointT &	front ()

const PointT &	back () const

PointT &	back ()

void	assign (index_t count, const PointT &value)
	Replaces the points with `count` copies of `value` More...

template<class InputIt >
void	assign (InputIt first, InputIt last)
	Replaces the points with copies of those in the range `[first, last)` More...

void	assign (std::initializer_list< PointT > ilist)
	Replaces the points with the elements from the initializer list `ilist` More...

void	push_back (const PointT &pt)
	Insert a new point in the cloud, at the end of the container. More...

template<class... Args>
reference	emplace_back (Args &&...args)
	Emplace a new point in the cloud, at the end of the container. More...

iterator	insert (iterator position, const PointT &pt)
	Insert a new point in the cloud, given an iterator. More...

void	insert (iterator position, std::size_t n, const PointT &pt)
	Insert a new point in the cloud N times, given an iterator. More...

template<class InputIterator >
void	insert (iterator position, InputIterator first, InputIterator last)
	Insert a new range of points in the cloud, at a certain position. More...

template<class... Args>
iterator	emplace (iterator position, Args &&...args)
	Emplace a new point in the cloud, given an iterator. More...

iterator	erase (iterator position)
	Erase a point in the cloud. More...

iterator	erase (iterator first, iterator last)
	Erase a set of points given by a (first, last) iterator pair. More...

void	swap (PointCloud< PointT > &rhs)
	Swap a point cloud with another cloud. More...

void	clear ()
	Removes all points in a cloud and sets the width and height to 0. More...

Ptr	makeShared () const
	Copy the cloud to the heap and return a smart pointer Note that deep copy is performed, so avoid using this function on non-empty clouds. More...

Static Public Member Functions
static bool	concatenate (pcl::PointCloud< PointT > &cloud1, const pcl::PointCloud< PointT > &cloud2)

static bool	concatenate (const pcl::PointCloud< PointT > &cloud1, const pcl::PointCloud< PointT > &cloud2, pcl::PointCloud< PointT > &cloud_out)

Public Attributes
pcl::PCLHeader	header
	The point cloud header. More...

std::vector< PointT, Eigen::aligned_allocator< PointT > >	points
	The point data. More...

std::uint32_t	width = 0
	The point cloud width (if organized as an image-structure). More...

std::uint32_t	height = 0
	The point cloud height (if organized as an image-structure). More...

bool	is_dense = true
	True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields). More...

Eigen::Vector4f	sensor_origin_ = Eigen::Vector4f::Zero ()
	Sensor acquisition pose (origin/translation). More...

Eigen::Quaternionf	sensor_orientation_ = Eigen::Quaternionf::Identity ()
	Sensor acquisition pose (rotation). More...

Detailed Description

template<typename PointT>
class pcl::PointCloud< PointT >

PointCloud represents the base class in PCL for storing collections of 3D points.

The class is templated, which means you need to specify the type of data that it should contain. For example, to create a point cloud that holds 4 random XYZ data points, use:

pcl::PointCloud<pcl::PointXYZ> cloud;
cloud.push_back (pcl::PointXYZ (rand (), rand (), rand ()));
cloud.push_back (pcl::PointXYZ (rand (), rand (), rand ()));
cloud.push_back (pcl::PointXYZ (rand (), rand (), rand ()));
cloud.push_back (pcl::PointXYZ (rand (), rand (), rand ()));

The PointCloud class contains the following elements:

width - specifies the width of the point cloud dataset in the number of points. WIDTH has two meanings:
- it can specify the total number of points in the cloud (equal with POINTS see below) for unorganized datasets;
- it can specify the width (total number of points in a row) of an organized point cloud dataset. Mandatory.
height - specifies the height of the point cloud dataset in the number of points. HEIGHT has two meanings:
- it can specify the height (total number of rows) of an organized point cloud dataset;
- it is set to 1 for unorganized datasets (thus used to check whether a dataset is organized or not). Mandatory.
points - the data array where all points of type PointT are stored. Mandatory.
is_dense - specifies if all the data in points is finite (true), or whether it might contain Inf/NaN values (false). Mandatory.
sensor_origin_ - specifies the sensor acquisition pose (origin/translation). Optional.
sensor_orientation_ - specifies the sensor acquisition pose (rotation). Optional.

Author: Patrick Mihelich, Radu B. Rusu

Definition at line 55 of file distances.h.

Member Typedef Documentation

◆ CloudVectorType

template<typename PointT >

using pcl::PointCloud< PointT >::CloudVectorType = std::vector<PointCloud<PointT>, Eigen::aligned_allocator<PointCloud<PointT> > >

Definition at line 405 of file point_cloud.h.

◆ const_iterator

template<typename PointT >

using pcl::PointCloud< PointT >::const_iterator = typename VectorType::const_iterator

Definition at line 419 of file point_cloud.h.

◆ const_reference

template<typename PointT >

using pcl::PointCloud< PointT >::const_reference = const PointT&

Definition at line 413 of file point_cloud.h.

◆ const_reverse_iterator

template<typename PointT >

using pcl::PointCloud< PointT >::const_reverse_iterator = typename VectorType::const_reverse_iterator

Definition at line 421 of file point_cloud.h.

◆ ConstPtr

template<typename PointT >

using pcl::PointCloud< PointT >::ConstPtr = shared_ptr<const PointCloud<PointT> >

Definition at line 407 of file point_cloud.h.

◆ difference_type

template<typename PointT >

using pcl::PointCloud< PointT >::difference_type = typename VectorType::difference_type

Definition at line 414 of file point_cloud.h.

◆ iterator

template<typename PointT >

using pcl::PointCloud< PointT >::iterator = typename VectorType::iterator

Definition at line 418 of file point_cloud.h.

◆ PointType

template<typename PointT >

using pcl::PointCloud< PointT >::PointType = PointT

Definition at line 403 of file point_cloud.h.

◆ Ptr

template<typename PointT >

using pcl::PointCloud< PointT >::Ptr = shared_ptr<PointCloud<PointT> >

Definition at line 406 of file point_cloud.h.

◆ reference

template<typename PointT >

using pcl::PointCloud< PointT >::reference = PointT&

Definition at line 412 of file point_cloud.h.

◆ reverse_iterator

template<typename PointT >

using pcl::PointCloud< PointT >::reverse_iterator = typename VectorType::reverse_iterator

Definition at line 420 of file point_cloud.h.

◆ size_type

template<typename PointT >

using pcl::PointCloud< PointT >::size_type = typename VectorType::size_type

Definition at line 415 of file point_cloud.h.

◆ value_type

template<typename PointT >

using pcl::PointCloud< PointT >::value_type = PointT

Definition at line 411 of file point_cloud.h.

◆ VectorType

template<typename PointT >

using pcl::PointCloud< PointT >::VectorType = std::vector<PointT, Eigen::aligned_allocator<PointT> >

Definition at line 404 of file point_cloud.h.

Constructor & Destructor Documentation

◆ PointCloud() [1/3]

template<typename PointT >

pcl::PointCloud< PointT >::PointCloud ( )

default

Default constructor.

Sets is_dense to true, width and height to 0, and the sensor_origin_ and sensor_orientation_ to identity.

◆ PointCloud() [2/3]

template<typename PointT >

pcl::PointCloud< PointT >::PointCloud	(	const PointCloud< PointT > &	pc,
		const Indices &	indices
	)

inline

Copy constructor from point cloud subset.

Parameters

[in]	pc	the cloud to copy into this
[in]	indices	the subset to copy

Definition at line 184 of file point_cloud.h.

◆ PointCloud() [3/3]

template<typename PointT >

pcl::PointCloud< PointT >::PointCloud	(	std::uint32_t	width_,
		std::uint32_t	height_,
		const PointT &	value_ = `PointT ()`
	)

inline

Allocate constructor from point cloud subset.

Parameters

[in]	width_	the cloud width
[in]	height_	the cloud height
[in]	value_	default value

Definition at line 200 of file point_cloud.h.

Member Function Documentation

◆ assign() [1/3]

template<typename PointT >

void pcl::PointCloud< PointT >::assign	(	index_t	count,
		const PointT &	value
	)

inline

Replaces the points with count copies of value

Note: This breaks the organized structure of the cloud by setting the height to 1!

Definition at line 502 of file point_cloud.h.

Referenced by pcl::transformPointCloud(), and pcl::transformPointCloudWithNormals().

◆ assign() [2/3]

template<typename PointT >

template<class InputIt >

void pcl::PointCloud< PointT >::assign	(	InputIt	first,
		InputIt	last
	)

inline

Replaces the points with copies of those in the range [first, last)

The behavior is undefined if either argument is an iterator into *this

Note: This breaks the organized structure of the cloud by setting the height to 1!

Definition at line 518 of file point_cloud.h.

◆ assign() [3/3]

template<typename PointT >

void pcl::PointCloud< PointT >::assign ( std::initializer_list< PointT > ilist )

inline

Replaces the points with the elements from the initializer list ilist

Note: This breaks the organized structure of the cloud by setting the height to 1!

Definition at line 531 of file point_cloud.h.

◆ at() [1/4]

template<typename PointT >

PointT& pcl::PointCloud< PointT >::at	(	int	column,
		int	row
	)

inline

Obtain the point given by the (column, row) coordinates.

Only works on organized datasets (those that have height != 1).

Parameters

[in]	column	the column coordinate
[in]	row	the row coordinate

Definition at line 275 of file point_cloud.h.

◆ at() [2/4]

template<typename PointT >

const PointT& pcl::PointCloud< PointT >::at	(	int	column,
		int	row
	)		const

inline

Obtain the point given by the (column, row) coordinates.

Only works on organized datasets (those that have height != 1).

Parameters

[in]	column	the column coordinate
[in]	row	the row coordinate

Definition at line 261 of file point_cloud.h.

Referenced by pcl::filters::Pyramid< PointT >::compute(), pcl::occlusion_reasoning::filter(), pcl::occlusion_reasoning::getOccludedCloud(), and pcl::PointCloudDepthAndRGBtoXYZRGBA().

◆ at() [3/4]

template<typename PointT >

PointT& pcl::PointCloud< PointT >::at ( std::size_t n )

inline

Definition at line 490 of file point_cloud.h.

◆ at() [4/4]

template<typename PointT >

const PointT& pcl::PointCloud< PointT >::at ( std::size_t n ) const

inline

Definition at line 489 of file point_cloud.h.

◆ back() [1/2]

template<typename PointT >

PointT& pcl::PointCloud< PointT >::back ( )

inline

Definition at line 494 of file point_cloud.h.

◆ back() [2/2]

template<typename PointT >

const PointT& pcl::PointCloud< PointT >::back ( ) const

inline

Definition at line 493 of file point_cloud.h.

Referenced by pcl::VoxelGridCovariance< PointTarget >::applyFilter(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getEdgeIndex(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getFaceIndex(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getHalfEdgeIndex(), and pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getVertexIndex().

◆ begin() [1/2]

template<typename PointT >

const_iterator pcl::PointCloud< PointT >::begin ( ) const

inlinenoexcept

Definition at line 424 of file point_cloud.h.

◆ begin() [2/2]

template<typename PointT >

iterator pcl::PointCloud< PointT >::begin ( )

inlinenoexcept

Definition at line 422 of file point_cloud.h.

Referenced by pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::cleanUp(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeCovariances(), pcl::PointCloud< pcl::RGB >::concatenate(), pcl::common::deleteCols(), pcl::common::deleteRows(), pcl::common::duplicateColumns(), pcl::common::duplicateRows(), pcl::common::expandColumns(), pcl::common::expandRows(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::extractDescriptors(), pcl::getFeaturePointCloud(), pcl::SupervoxelClustering< PointT >::getLabeledCloud(), pcl::SupervoxelClustering< PointT >::getLabeledVoxelCloud(), pcl::SupervoxelClustering< PointT >::makeSupervoxelNormalCloud(), pcl::common::mirrorColumns(), pcl::common::mirrorRows(), pcl::MovingLeastSquares< PointInT, PointOutT >::performProcessing(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::validateTransformation().

◆ cbegin()

template<typename PointT >

const_iterator pcl::PointCloud< PointT >::cbegin ( ) const

inlinenoexcept

Definition at line 426 of file point_cloud.h.

Referenced by pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::readRange(), pcl::MinCutSegmentation< PointT >::setBackgroundPoints(), and pcl::MinCutSegmentation< PointT >::setForegroundPoints().

◆ cend()

template<typename PointT >

const_iterator pcl::PointCloud< PointT >::cend ( ) const

inlinenoexcept

Definition at line 427 of file point_cloud.h.

◆ clear()

template<typename PointT >

void pcl::PointCloud< PointT >::clear ( )

inline

Removes all points in a cloud and sets the width and height to 0.

Definition at line 668 of file point_cloud.h.

Referenced by pcl::LocalMaximum< PointT >::applyFilter(), pcl::GridMinimum< PointT >::applyFilter(), pcl::ProjectInliers< PointT >::applyFilter(), pcl::UniformSampling< PointT >::applyFilter(), pcl::VoxelGrid< pcl::PointXYZRGBL >::applyFilter(), pcl::VoxelGridCovariance< PointTarget >::applyFilter(), pcl::approximatePolygon2D(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::compute(), pcl::GASDEstimation< PointInT, GASDSignature984 >::compute(), pcl::DisparityMapConverter< PointDEM >::compute(), pcl::Feature< PointInT, pcl::SHOT352 >::compute(), pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::computeFeature(), pcl::IntensitySpinEstimation< PointInT, PointOutT >::computeFeature(), pcl::RIFTEstimation< PointInT, GradientT, PointOutT >::computeFeature(), pcl::RSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::TSDFVolume< VoxelT, WeightT >::convertToTsdfCloud(), pcl::gpu::extractEuclideanClusters(), pcl::VoxelGridCovariance< PointTarget >::getDisplayCloud(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::CloudSurfaceProcessing< PointInT, PointOutT >::process(), pcl::BilateralUpsampling< PointInT, PointOutT >::process(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::SurfaceReconstruction< PointNT >::reconstruct(), pcl::SegmentDifferences< PointT >::segment(), and pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::setSearchSurface().

◆ concatenate() [1/2]

template<typename PointT >

static bool pcl::PointCloud< PointT >::concatenate	(	const pcl::PointCloud< PointT > &	cloud1,
		const pcl::PointCloud< PointT > &	cloud2,
		pcl::PointCloud< PointT > &	cloud_out
	)

inlinestatic

Definition at line 247 of file point_cloud.h.

◆ concatenate() [2/2]

template<typename PointT >

static bool pcl::PointCloud< PointT >::concatenate	(	pcl::PointCloud< PointT > &	cloud1,
		const pcl::PointCloud< PointT > &	cloud2
	)

inlinestatic

Definition at line 230 of file point_cloud.h.

Referenced by pcl::concatenate().

◆ crbegin()

template<typename PointT >

const_reverse_iterator pcl::PointCloud< PointT >::crbegin ( ) const

inlinenoexcept

Definition at line 432 of file point_cloud.h.

◆ crend()

template<typename PointT >

const_reverse_iterator pcl::PointCloud< PointT >::crend ( ) const

inlinenoexcept

Definition at line 433 of file point_cloud.h.

◆ data() [1/2]

template<typename PointT >

const PointT* pcl::PointCloud< PointT >::data ( ) const

inlinenoexcept

Definition at line 441 of file point_cloud.h.

◆ data() [2/2]

template<typename PointT >

PointT* pcl::PointCloud< PointT >::data ( )

inlinenoexcept

Definition at line 440 of file point_cloud.h.

Referenced by pcl::transformPointCloud().

◆ emplace()

template<typename PointT >

template<class... Args>

iterator pcl::PointCloud< PointT >::emplace	(	iterator	position,
		Args &&...	args
	)

inline

Emplace a new point in the cloud, given an iterator.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	position	iterator before which the point will be emplaced
[in]	args	the parameters to forward to the point to construct

Returns: returns the new position iterator

Definition at line 614 of file point_cloud.h.

◆ emplace_back()

template<typename PointT >

template<class... Args>

reference pcl::PointCloud< PointT >::emplace_back ( Args &&... args )

inline

Emplace a new point in the cloud, at the end of the container.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in] args the parameters to forward to the point to construct

Returns: reference to the emplaced point

Definition at line 556 of file point_cloud.h.

Referenced by pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures().

◆ empty()

template<typename PointT >

bool pcl::PointCloud< PointT >::empty ( ) const

inline

Definition at line 439 of file point_cloud.h.

Referenced by pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::applyMorphologicalOperator(), pcl::compute3DCentroid(), pcl::computeCovarianceMatrix(), pcl::computeNDCentroid(), pcl::copyPointCloud(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::kinfuLS::WorldModel< pcl::PointXYZI >::getExistingData(), pcl::OrganizedMultiPlaneSegmentation< pcl::PointXYZRGBA, pcl::Normal, pcl::Label >::segmentAndRefine(), pcl::SupervoxelClustering< PointT >::setInputCloud(), pcl::PCDWriter::writeASCII(), pcl::PCDWriter::writeBinary(), and pcl::PCDWriter::writeBinaryCompressed().

◆ end() [1/2]

template<typename PointT >

const_iterator pcl::PointCloud< PointT >::end ( ) const

inlinenoexcept

Definition at line 425 of file point_cloud.h.

◆ end() [2/2]

template<typename PointT >

iterator pcl::PointCloud< PointT >::end ( )

inlinenoexcept

Definition at line 423 of file point_cloud.h.

Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeCovariances(), pcl::PointCloud< pcl::RGB >::concatenate(), pcl::common::deleteRows(), pcl::common::duplicateRows(), pcl::common::expandRows(), pcl::SupervoxelClustering< PointT >::getLabeledCloud(), pcl::SupervoxelClustering< PointT >::getLabeledVoxelCloud(), pcl::common::mirrorRows(), pcl::MovingLeastSquares< PointInT, PointOutT >::performProcessing(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), and pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation().

◆ erase() [1/2]

template<typename PointT >

iterator pcl::PointCloud< PointT >::erase	(	iterator	first,
		iterator	last
	)

inline

Erase a set of points given by a (first, last) iterator pair.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	first	where to start erasing points from
[in]	last	where to stop erasing points from

Returns: returns the new position iterator

Definition at line 643 of file point_cloud.h.

◆ erase() [2/2]

template<typename PointT >

iterator pcl::PointCloud< PointT >::erase ( iterator position )

inline

Erase a point in the cloud.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in] position what data point to erase

Returns: returns the new position iterator

Definition at line 628 of file point_cloud.h.

Referenced by pcl::common::deleteCols(), pcl::common::deleteRows(), and pcl::ConcaveHull< PointInT >::performReconstruction().

◆ front() [1/2]

template<typename PointT >

PointT& pcl::PointCloud< PointT >::front ( )

inline

Definition at line 492 of file point_cloud.h.

◆ front() [2/2]

template<typename PointT >

const PointT& pcl::PointCloud< PointT >::front ( ) const

inline

Definition at line 491 of file point_cloud.h.

Referenced by pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getEdgeIndex(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getFaceIndex(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getHalfEdgeIndex(), and pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::getVertexIndex().

◆ getMatrixXfMap() [1/4]

template<typename PointT >

const Eigen::Map< Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> > pcl::PointCloud< PointT >::getMatrixXfMap ( )

inline

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Note: This method is for advanced users only! Use with care!

Attention: PointT types are most of the time aligned, so the offsets are not continuous!

Definition at line 367 of file point_cloud.h.

◆ getMatrixXfMap() [2/4]

template<typename PointT >

const Eigen::Map<const Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> > pcl::PointCloud< PointT >::getMatrixXfMap ( ) const

inline

Definition at line 379 of file point_cloud.h.

◆ getMatrixXfMap() [3/4]

template<typename PointT >

Eigen::Map<Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> > pcl::PointCloud< PointT >::getMatrixXfMap	(	int	dim,
		int	stride,
		int	offset
	)

inline

Return an Eigen MatrixXf (assumes float values) mapped to the specified dimensions of the PointCloud.

Note: This method is for advanced users only! Use with care!

Attention: Since 1.4.0, Eigen matrices are forced to Row Major to increase the efficiency of the algorithms in PCL This means that the behavior of getMatrixXfMap changed, and is now correctly mapping 1-1 with a PointCloud structure, that is: number of points in a cloud = rows in a matrix, number of point dimensions = columns in a matrix

Parameters

[in]	dim	the number of dimensions to consider for each point
[in]	stride	the number of values in each point (will be the number of values that separate two of the columns)
[in]	offset	the number of dimensions to skip from the beginning of each point (stride = offset + dim + x, where x is the number of dimensions to skip from the end of each point)

Note: for getting only XYZ coordinates out of PointXYZ use dim=3, stride=4 and offset=0 due to the alignment.

Attention: PointT types are most of the time aligned, so the offsets are not continuous!

Definition at line 329 of file point_cloud.h.

◆ getMatrixXfMap() [4/4]

template<typename PointT >

const Eigen::Map<const Eigen::MatrixXf, Eigen::Aligned, Eigen::OuterStride<> > pcl::PointCloud< PointT >::getMatrixXfMap	(	int	dim,
		int	stride,
		int	offset
	)		const

inline

Return an Eigen MatrixXf (assumes float values) mapped to the specified dimensions of the PointCloud.

Note: This method is for advanced users only! Use with care!

Attention: Since 1.4.0, Eigen matrices are forced to Row Major to increase the efficiency of the algorithms in PCL This means that the behavior of getMatrixXfMap changed, and is now correctly mapping 1-1 with a PointCloud structure, that is: number of points in a cloud = rows in a matrix, number of point dimensions = columns in a matrix

Parameters

[in]	dim	the number of dimensions to consider for each point
[in]	stride	the number of values in each point (will be the number of values that separate two of the columns)
[in]	offset	the number of dimensions to skip from the beginning of each point (stride = offset + dim + x, where x is the number of dimensions to skip from the end of each point)

Note: for getting only XYZ coordinates out of PointXYZ use dim=3, stride=4 and offset=0 due to the alignment.

Attention: PointT types are most of the time aligned, so the offsets are not continuous!

Definition at line 352 of file point_cloud.h.

◆ insert() [1/3]

template<typename PointT >

iterator pcl::PointCloud< PointT >::insert	(	iterator	position,
		const PointT &	pt
	)

inline

Insert a new point in the cloud, given an iterator.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	position	where to insert the point
[in]	pt	the point to insert

Returns: returns the new position iterator

Definition at line 571 of file point_cloud.h.

Referenced by pcl::PointCloud< pcl::RGB >::concatenate(), pcl::common::duplicateColumns(), pcl::common::duplicateRows(), pcl::common::expandColumns(), pcl::common::expandRows(), pcl::common::mirrorColumns(), pcl::common::mirrorRows(), and pcl::MovingLeastSquares< PointInT, PointOutT >::performProcessing().

◆ insert() [2/3]

template<typename PointT >

template<class InputIterator >

void pcl::PointCloud< PointT >::insert	(	iterator	position,
		InputIterator	first,
		InputIterator	last
	)

inline

Insert a new range of points in the cloud, at a certain position.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	position	where to insert the data
[in]	first	where to start inserting the points from
[in]	last	where to stop inserting the points from

Definition at line 600 of file point_cloud.h.

◆ insert() [3/3]

template<typename PointT >

void pcl::PointCloud< PointT >::insert	(	iterator	position,
		std::size_t	n,
		const PointT &	pt
	)

inline

Insert a new point in the cloud N times, given an iterator.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in]	position	where to insert the point
[in]	n	the number of times to insert the point
[in]	pt	the point to insert

Definition at line 586 of file point_cloud.h.

◆ isOrganized()

template<typename PointT >

bool pcl::PointCloud< PointT >::isOrganized ( ) const

inline

Return whether a dataset is organized (e.g., arranged in a structured grid).

Note: The height value must be different than 1 for a dataset to be organized.

Definition at line 309 of file point_cloud.h.

Referenced by pcl::visualization::ImageViewer::addMask(), pcl::HypothesisVerification< ModelT, SceneT >::addModels(), pcl::visualization::ImageViewer::addPlanarPolygon(), pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::ImageViewer::addRectangle(), pcl::common::deleteCols(), pcl::common::duplicateColumns(), pcl::common::expandColumns(), pcl::io::PointCloudImageExtractor< PointT >::extract(), pcl::common::mirrorColumns(), and pcl::PCDGrabber< PointT >::publish().

◆ makeShared()

template<typename PointT >

Ptr pcl::PointCloud< PointT >::makeShared ( ) const

inline

Copy the cloud to the heap and return a smart pointer Note that deep copy is performed, so avoid using this function on non-empty clouds.

The changes of the returned cloud are not mirrored back to this one.

Returns: shared pointer to the copy of the cloud

Definition at line 681 of file point_cloud.h.

Referenced by pcl::Edge< ImageType, ImageType >::canny(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::estimateFeatures(), and pcl::Edge< ImageType, ImageType >::sobelMagnitudeDirection().

◆ max_size()

template<typename PointT >

index_t pcl::PointCloud< PointT >::max_size ( ) const

inlinenoexcept

Definition at line 437 of file point_cloud.h.

◆ operator()() [1/2]

template<typename PointT >

PointT& pcl::PointCloud< PointT >::operator()	(	std::size_t	column,
		std::size_t	row
	)

inline

Obtain the point given by the (column, row) coordinates.

Only works on organized datasets (those that have height != 1).

Parameters

[in]	column	the column coordinate
[in]	row	the row coordinate

Definition at line 300 of file point_cloud.h.

◆ operator()() [2/2]

template<typename PointT >

const PointT& pcl::PointCloud< PointT >::operator()	(	std::size_t	column,
		std::size_t	row
	)		const

inline

Obtain the point given by the (column, row) coordinates.

Only works on organized datasets (those that have height != 1).

Parameters

[in]	column	the column coordinate
[in]	row	the row coordinate

Definition at line 289 of file point_cloud.h.

◆ operator+()

template<typename PointT >

PointCloud pcl::PointCloud< PointT >::operator+ ( const PointCloud< PointT > & rhs )

inline

Add a point cloud to another cloud.

Parameters

[in] rhs the cloud to add to the current cloud

Returns: the new cloud as a concatenation of the current cloud and the new given cloud

Definition at line 224 of file point_cloud.h.

◆ operator+=()

template<typename PointT >

PointCloud& pcl::PointCloud< PointT >::operator+= ( const PointCloud< PointT > & rhs )

inline

Add a point cloud to the current cloud.

Parameters

[in] rhs the cloud to add to the current cloud

Returns: the new cloud as a concatenation of the current cloud and the new given cloud

Definition at line 213 of file point_cloud.h.

◆ operator[]() [1/2]

template<typename PointT >

PointT& pcl::PointCloud< PointT >::operator[] ( std::size_t n )

inline

Definition at line 488 of file point_cloud.h.

◆ operator[]() [2/2]

template<typename PointT >

const PointT& pcl::PointCloud< PointT >::operator[] ( std::size_t n ) const

inline

Definition at line 487 of file point_cloud.h.

◆ push_back()

template<typename PointT >

void pcl::PointCloud< PointT >::push_back ( const PointT & pt )

inline

Insert a new point in the cloud, at the end of the container.

Note: This breaks the organized structure of the cloud by setting the height to 1!

Parameters

[in] pt the point to insert

Definition at line 543 of file point_cloud.h.

Referenced by pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::addData(), pcl::MovingLeastSquares< PointInT, PointOutT >::addProjectedPointNormal(), pcl::VoxelGridCovariance< PointTarget >::applyFilter(), pcl::approximatePolygon2D(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::TSDFVolume< VoxelT, WeightT >::convertToTsdfCloud(), pcl::MarchingCubes< PointNT >::createSurface(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::gpu::extractEuclideanClusters(), pcl::extractEuclideanClusters(), pcl::gpu::extractLabeledEuclideanClusters(), pcl::VoxelGridCovariance< PointTarget >::getDisplayCloud(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::insertRange(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::PointCloudDepthAndRGBtoXYZRGBA(), pcl::PointCloudRGBtoI(), pcl::PointCloudXYZRGBAtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZI(), pcl::OrganizedConnectedComponentSegmentation< PointT, PointLT >::segment(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::setPointsToTrack(), and pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::track().

◆ rbegin() [1/2]

template<typename PointT >

const_reverse_iterator pcl::PointCloud< PointT >::rbegin ( ) const

inlinenoexcept

Definition at line 430 of file point_cloud.h.

◆ rbegin() [2/2]

template<typename PointT >

reverse_iterator pcl::PointCloud< PointT >::rbegin ( )

inlinenoexcept

Definition at line 428 of file point_cloud.h.

◆ rend() [1/2]

template<typename PointT >

const_reverse_iterator pcl::PointCloud< PointT >::rend ( ) const

inlinenoexcept

Definition at line 431 of file point_cloud.h.

◆ rend() [2/2]

template<typename PointT >

reverse_iterator pcl::PointCloud< PointT >::rend ( )

inlinenoexcept

Definition at line 429 of file point_cloud.h.

◆ reserve()

template<typename PointT >

void pcl::PointCloud< PointT >::reserve ( std::size_t n )

inline

Definition at line 438 of file point_cloud.h.

Referenced by pcl::VoxelGridCovariance< PointTarget >::applyFilter(), pcl::approximatePolygon2D(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::computeTracking(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::TSDFVolume< VoxelT, WeightT >::convertToTsdfCloud(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::common::duplicateColumns(), pcl::common::duplicateRows(), pcl::common::expandColumns(), pcl::common::expandRows(), pcl::common::mirrorColumns(), pcl::common::mirrorRows(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::setPointsToTrack(), pcl::transformPointCloud(), and pcl::transformPointCloudWithNormals().

◆ resize() [1/2]

template<typename PointT >

void pcl::PointCloud< PointT >::resize	(	index_t	count,
		const PointT &	value
	)

inline

Resizes the container to contain count elements.

If the current size is greater than count, the pointcloud is reduced to its first count elements
If the current size is less than count, additional copies of value are appended
Note
This potentially breaks the organized structure of the cloud by setting the height to 1 IFF width * height != count!

Parameters

[in] count new size of the point cloud

[in] value the value to initialize the new points with

Definition at line 477 of file point_cloud.h.

◆ resize() [2/2]

template<typename PointT >

void pcl::PointCloud< PointT >::resize ( std::size_t count )

inline

Resizes the container to contain count elements.

If the current size is greater than count, the pointcloud is reduced to its first count elements
If the current size is less than count, additional default-inserted points are appended
Note
This potentially breaks the organized structure of the cloud by setting the height to 1 IFF width * height != count!

Parameters

[in] count new size of the point cloud

Definition at line 455 of file point_cloud.h.

Referenced by pcl::Registration< PointSource, PointTarget >::align(), pcl::ShadowPoints< PointT, NormalT >::applyFilter(), pcl::UniformSampling< PointT >::applyFilter(), pcl::ApproximateVoxelGrid< PointT >::applyFilter(), pcl::VoxelGrid< pcl::PointXYZRGBL >::applyFilter(), pcl::ConditionalRemoval< PointT >::applyFilter(), pcl::approximatePolygon(), pcl::Edge< ImageType, ImageType >::canny(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::cleanUp(), pcl::OrganizedEdgeBase< PointT, PointLT >::compute(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::compute(), pcl::BRISK2DEstimation< PointInT, PointOutT, KeypointT, IntensityT >::compute(), pcl::GASDEstimation< PointInT, GASDSignature984 >::compute(), pcl::DisparityMapConverter< PointDEM >::compute(), pcl::Feature< PointInT, pcl::SHOT352 >::compute(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::compute(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::compute(), pcl::OrganizedEdgeFromRGBNormals< PointT, PointNT, PointLT >::compute(), pcl::features::computeApproximateNormals(), pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::computeFeature(), pcl::NormalBasedSignatureEstimation< PointT, PointNT, PointFeature >::computeFeature(), pcl::LineRGBD< PointXYZT, PointRGBT >::computeTransformedTemplatePoints(), pcl::concatenateFields(), pcl::filters::Convolution3D< PointIn, PointOut, KernelT >::convolve(), pcl::GaussianKernel::convolveCols(), pcl::GaussianKernel::convolveRows(), pcl::copyPointCloud(), pcl::demeanPointCloud(), pcl::Edge< ImageType, ImageType >::detectEdgeCanny(), pcl::Edge< ImageType, ImageType >::detectEdgePrewitt(), pcl::Edge< ImageType, ImageType >::detectEdgeRoberts(), pcl::Edge< ImageType, ImageType >::detectEdgeSobel(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::Morphology< PointT >::dilationBinary(), pcl::Morphology< PointT >::dilationGray(), pcl::Morphology< PointT >::erosionBinary(), pcl::Morphology< PointT >::erosionGray(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::extractEdges(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::extractEdges(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::fromPCLPointCloud2(), pcl::filters::Convolution< PointIn, PointOut >::initCompute(), pcl::Morphology< PointT >::intersectionBinary(), pcl::isPointIn2DPolygon(), pcl::SupervoxelClustering< PointT >::makeSupervoxelNormalCloud(), pcl::search::Search< PointXYZRGB >::nearestKSearchT(), pcl::BilateralUpsampling< PointInT, PointOutT >::performProcessing(), pcl::Poisson< PointNT >::performReconstruction(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::ConvexHull< PointInT >::performReconstruction3D(), pcl::ColorGradientModality< PointXYZT >::processInputData(), pcl::SampleConsensusModelLine< PointT >::projectPoints(), pcl::SampleConsensusModelStick< PointT >::projectPoints(), pcl::SampleConsensusModelCircle2D< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelCircle3D< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelSphere< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelCylinder< pcl::PointXYZRGB, PointNT >::projectPoints(), pcl::SampleConsensusModelPlane< PointT >::projectPoints(), pcl::SampleConsensusModelCone< pcl::PointXYZRGB, PointNT >::projectPoints(), pcl::search::Search< PointXYZRGB >::radiusSearchT(), pcl::io::LZFDepth16ImageReader::read(), pcl::io::LZFRGB24ImageReader::read(), pcl::io::LZFYUV422ImageReader::read(), pcl::io::LZFBayer8ImageReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::io::LZFRGB24ImageReader::readOMP(), pcl::io::LZFYUV422ImageReader::readOMP(), pcl::io::LZFBayer8ImageReader::readOMP(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::OrganizedConnectedComponentSegmentation< PointT, PointLT >::segment(), pcl::ExtractPolygonalPrismData< PointT >::segment(), pcl::OrganizedMultiPlaneSegmentation< pcl::PointXYZRGBA, pcl::Normal, pcl::Label >::segment(), pcl::OrganizedMultiPlaneSegmentation< pcl::PointXYZRGBA, pcl::Normal, pcl::Label >::segmentAndRefine(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::setPointsToTrack(), pcl::Edge< ImageType, ImageType >::sobelMagnitudeDirection(), pcl::Morphology< PointT >::subtractionBinary(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::Morphology< PointT >::unionBinary(), pcl::registration::TransformationValidationEuclidean< PointSource, PointTarget, Scalar >::validateTransformation(), pcl::io::vtkPolyDataToPointCloud(), and pcl::io::vtkStructuredGridToPointCloud().

◆ size()

template<typename PointT >

std::size_t pcl::PointCloud< PointT >::size ( ) const

inline

Definition at line 436 of file point_cloud.h.

◆ swap()

template<typename PointT >

void pcl::PointCloud< PointT >::swap ( PointCloud< PointT > & rhs )

inline

Swap a point cloud with another cloud.

Parameters

[in,out] rhs point cloud to swap this with

Definition at line 655 of file point_cloud.h.

Referenced by pcl::applyMorphologicalOperator(), and pcl::MarchingCubes< PointNT >::performReconstruction().

Member Data Documentation

◆ header

template<typename PointT >

pcl::PCLHeader pcl::PointCloud< PointT >::header

The point cloud header.

It contains information about the acquisition time.

Definition at line 385 of file point_cloud.h.

Referenced by pcl::Registration< PointSource, PointTarget >::align(), pcl::ConditionalRemoval< PointT >::applyFilter(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::compute(), pcl::GASDEstimation< PointInT, GASDSignature984 >::compute(), pcl::Feature< PointInT, pcl::SHOT352 >::compute(), pcl::features::computeApproximateNormals(), pcl::PointCloud< pcl::RGB >::concatenate(), pcl::concatenateFields(), pcl::copyPointCloud(), pcl::demeanPointCloud(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::gpu::extractEuclideanClusters(), pcl::extractEuclideanClusters(), pcl::gpu::extractLabeledEuclideanClusters(), pcl::extractLabeledEuclideanClusters(), pcl::Filter< pcl::PointXYZRGBL >::filter(), pcl::fromPCLPointCloud2(), pcl::operator<<(), pcl::BilateralUpsampling< PointInT, PointOutT >::performProcessing(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::CloudSurfaceProcessing< PointInT, PointOutT >::process(), pcl::BilateralUpsampling< PointInT, PointOutT >::process(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::SampleConsensusModelLine< PointT >::projectPoints(), pcl::SampleConsensusModelStick< PointT >::projectPoints(), pcl::SampleConsensusModelCircle2D< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelCircle3D< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelSphere< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelCylinder< pcl::PointXYZRGB, PointNT >::projectPoints(), pcl::SampleConsensusModelPlane< PointT >::projectPoints(), pcl::SampleConsensusModelCone< pcl::PointXYZRGB, PointNT >::projectPoints(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::SurfaceReconstruction< PointNT >::reconstruct(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::SegmentDifferences< PointT >::segment(), pcl::PointCloud< pcl::RGB >::swap(), pcl::toPCLPointCloud2(), pcl::transformPointCloud(), and pcl::transformPointCloudWithNormals().

◆ height

template<typename PointT >

std::uint32_t pcl::PointCloud< PointT >::height = 0

The point cloud height (if organized as an image-structure).

Definition at line 393 of file point_cloud.h.

◆ is_dense

template<typename PointT >

bool pcl::PointCloud< PointT >::is_dense = true

True if no points are invalid (e.g., have NaN or Inf values in any of their floating point fields).

Definition at line 396 of file point_cloud.h.

◆ points

template<typename PointT >

std::vector<PointT, Eigen::aligned_allocator<PointT> > pcl::PointCloud< PointT >::points

The point data.

Definition at line 388 of file point_cloud.h.

Referenced by pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::features::computeApproximateCovariances(), pcl::features::computeApproximateNormals(), pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::MomentInvariantsEstimation< PointInT, PointOutT >::computePointMomentInvariants(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::convertTrianglesToMesh(), pcl::visualization::createPolygon(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::BriskKeypoint2D< PointInT, PointOutT, IntensityT >::detectKeypoints(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::extractDescriptors(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::extractRGBFromPointCloud(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::findObjects(), pcl::UnaryClassifier< PointT >::getCloudWithLabel(), pcl::features::ISMVoteList< PointT >::getColoredCloud(), pcl::MinCutSegmentation< PointT >::getColoredCloud(), pcl::RegionGrowing< PointT, pcl::Normal >::getColoredCloud(), pcl::RegionGrowing< PointT, pcl::Normal >::getColoredCloudRGBA(), pcl::getMinMax3D(), pcl::RFFaceDetectorTrainer::getVotes(), pcl::RFFaceDetectorTrainer::getVotes2(), pcl::UnaryClassifier< PointT >::kmeansClustering(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::PointCloudRGBtoI(), pcl::PointCloudXYZRGBAtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZI(), pcl::SampleConsensusModelSphere< pcl::PointXYZRGB >::projectPoints(), pcl::OrganizedMultiPlaneSegmentation< pcl::PointXYZRGBA, pcl::Normal, pcl::Label >::segment(), pcl::OrganizedMultiPlaneSegmentation< pcl::PointXYZRGBA, pcl::Normal, pcl::Label >::segmentAndRefine(), pcl::PlanarPolygon< PointT >::setContour(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::shiftCloud(), pcl::TextureMapping< PointInT >::showOcclusions(), pcl::PointCloud< pcl::RGB >::swap(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::swapDimensions(), pcl::TextureMapping< PointInT >::textureMeshwithMultipleCameras(), and pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::validateMatch().

◆ sensor_orientation_

template<typename PointT >

Eigen::Quaternionf pcl::PointCloud< PointT >::sensor_orientation_ = Eigen::Quaternionf::Identity ()

Sensor acquisition pose (rotation).

Definition at line 401 of file point_cloud.h.

Referenced by pcl::visualization::PCLVisualizer::addCorrespondences(), pcl::visualization::PCLVisualizer::addPointCloud(), pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::IntegralImageNormalEstimation< pcl::PointXYZRGBA, pcl::Normal >::computeFeature(), pcl::copyPointCloud(), pcl::Filter< pcl::PointXYZRGBL >::filter(), pcl::PCDWriter::generateHeader(), pcl::operator<<(), pcl::PCDGrabber< PointT >::operator[](), pcl::ImageGrabber< PointT >::operator[](), pcl::StereoGrabber< PointT >::publish(), pcl::PCDGrabber< PointT >::publish(), pcl::ImageGrabber< PointT >::publish(), pcl::IFSReader::read(), pcl::FileReader::read(), pcl::PLYReader::read(), pcl::io::LZFDepth16ImageReader::read(), pcl::OBJReader::read(), pcl::PCDReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::PointCloud< pcl::RGB >::swap(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::FileWriter::write(), and pcl::PLYWriter::write().

◆ sensor_origin_

template<typename PointT >

Eigen::Vector4f pcl::PointCloud< PointT >::sensor_origin_ = Eigen::Vector4f::Zero ()

Sensor acquisition pose (origin/translation).

Definition at line 399 of file point_cloud.h.

◆ width

template<typename PointT >

std::uint32_t pcl::PointCloud< PointT >::width = 0

The point cloud width (if organized as an image-structure).

Definition at line 391 of file point_cloud.h.

Referenced by pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::ImageViewer::addRGBImage(), pcl::Registration< PointSource, PointTarget >::align(), pcl::LocalMaximum< PointT >::applyFilter(), pcl::MedianFilter< PointT >::applyFilter(), pcl::GridMinimum< PointT >::applyFilter(), pcl::ShadowPoints< PointT, NormalT >::applyFilter(), pcl::ProjectInliers< PointT >::applyFilter(), pcl::UniformSampling< PointT >::applyFilter(), pcl::SamplingSurfaceNormal< PointT >::applyFilter(), pcl::ApproximateVoxelGrid< PointT >::applyFilter(), pcl::VoxelGrid< pcl::PointXYZRGBL >::applyFilter(), pcl::VoxelGridCovariance< PointTarget >::applyFilter(), pcl::ConditionalRemoval< PointT >::applyFilter(), pcl::LineRGBD< PointXYZT, PointRGBT >::applyProjectiveDepthICPOnDetections(), pcl::RangeImageBorderExtractor::calculateBorderDirection(), pcl::RangeImageBorderExtractor::calculateMainPrincipalCurvature(), pcl::Edge< ImageType, ImageType >::canny(), pcl::RangeImageBorderExtractor::changeScoreAccordingToShadowBorderValue(), pcl::RangeImageBorderExtractor::checkIfMaximum(), pcl::RangeImageBorderExtractor::checkPotentialBorder(), pcl::OrganizedEdgeBase< PointT, PointLT >::compute(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::compute(), pcl::filters::Pyramid< PointT >::compute(), pcl::BRISK2DEstimation< PointInT, PointOutT, KeypointT, IntensityT >::compute(), pcl::GASDEstimation< PointInT, GASDSignature984 >::compute(), pcl::DisparityMapConverter< PointDEM >::compute(), pcl::Feature< PointInT, pcl::SHOT352 >::compute(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::compute(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::compute(), pcl::OrganizedEdgeFromRGBNormals< PointT, PointNT, PointLT >::compute(), pcl::features::computeApproximateNormals(), pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::computeFeature(), pcl::IntensitySpinEstimation< PointInT, PointOutT >::computeFeature(), pcl::RIFTEstimation< PointInT, GradientT, PointOutT >::computeFeature(), pcl::RSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::IntegralImageNormalEstimation< pcl::PointXYZRGBA, pcl::Normal >::computeFeatureFull(), pcl::IntegralImageNormalEstimation< pcl::PointXYZRGBA, pcl::Normal >::computeFeaturePart(), pcl::ColorGradientModality< PointXYZT >::computeMaxColorGradients(), pcl::ColorGradientModality< PointXYZT >::computeMaxColorGradientsSobel(), pcl::LineRGBD< PointXYZT, PointRGBT >::computeTransformedTemplatePoints(), pcl::PointCloud< pcl::RGB >::concatenate(), pcl::concatenateFields(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::gpu::kinfuLS::StandaloneMarchingCubes< PointT >::convertTrianglesToMesh(), pcl::GaussianKernel::convolve(), pcl::filters::Convolution3D< PointIn, PointOut, KernelT >::convolve(), pcl::GaussianKernel::convolveCols(), pcl::GaussianKernel::convolveRows(), pcl::copyPointCloud(), pcl::common::deleteCols(), pcl::common::deleteRows(), pcl::demeanPointCloud(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::derivatives(), pcl::Edge< ImageType, ImageType >::detectEdgeCanny(), pcl::Edge< ImageType, ImageType >::detectEdgePrewitt(), pcl::Edge< ImageType, ImageType >::detectEdgeRoberts(), pcl::Edge< ImageType, ImageType >::detectEdgeSobel(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::Morphology< PointT >::dilationBinary(), pcl::Morphology< PointT >::dilationGray(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::downsample(), pcl::common::duplicateColumns(), pcl::common::duplicateRows(), pcl::Morphology< PointT >::erosionBinary(), pcl::Morphology< PointT >::erosionGray(), pcl::estimateProjectionMatrix(), pcl::common::expandColumns(), pcl::common::expandRows(), pcl::io::PointCloudImageExtractor< PointT >::extract(), pcl::OrganizedEdgeBase< PointT, PointLT >::extractEdges(), pcl::OrganizedEdgeFromRGB< PointT, PointLT >::extractEdges(), pcl::OrganizedEdgeFromNormals< PointT, PointNT, PointLT >::extractEdges(), pcl::io::PointCloudImageExtractorWithScaling< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromNormalField< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromRGBField< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromLabelField< PointT >::extractImpl(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::extractRGBFromPointCloud(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::occlusion_reasoning::filter(), pcl::fromPCLPointCloud2(), pcl::PCDWriter::generateHeader(), pcl::UnaryClassifier< PointT >::getCloudWithLabel(), pcl::features::ISMVoteList< PointT >::getColoredCloud(), pcl::MinCutSegmentation< PointT >::getColoredCloud(), pcl::RegionGrowing< PointT, pcl::Normal >::getColoredCloud(), pcl::RegionGrowing< PointT, pcl::Normal >::getColoredCloudRGBA(), pcl::occlusion_reasoning::getOccludedCloud(), pcl::RFFaceDetectorTrainer::getVotes(), pcl::RFFaceDetectorTrainer::getVotes2(), pcl::filters::Convolution< PointIn, PointOut >::initCompute(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::insertRange(), pcl::Morphology< PointT >::intersectionBinary(), pcl::UnaryClassifier< PointT >::kmeansClustering(), pcl::common::mirrorColumns(), pcl::common::mirrorRows(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::mismatchVector(), pcl::operator<<(), pcl::BilateralUpsampling< PointInT, PointOutT >::performProcessing(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::ConvexHull< PointInT >::performReconstruction3D(), pcl::PointCloudDepthAndRGBtoXYZRGBA(), pcl::PointCloudRGBtoI(), pcl::io::pointCloudTovtkStructuredGrid(), pcl::PointCloudXYZRGBAtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZHSV(), pcl::PointCloudXYZRGBtoXYZI(), pcl::CloudSurfaceProcessing< PointInT, PointOutT >::process(), pcl::BilateralUpsampling< PointInT, PointOutT >::process(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::ColorGradientModality< PointXYZT >::processInputData(), pcl::SampleConsensusModelLine< PointT >::projectPoints(), pcl::SampleConsensusModelStick< PointT >::projectPoints(), pcl::SampleConsensusModelCircle2D< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelCircle3D< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelSphere< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelCylinder< pcl::PointXYZRGB, PointNT >::projectPoints(), pcl::SampleConsensusModelPlane< PointT >::projectPoints(), pcl::SampleConsensusModelCone< pcl::PointXYZRGB, PointNT >::projectPoints(), pcl::PCDGrabber< PointT >::publish(), pcl::outofcore::OutofcoreOctreeBaseNode::queryBBIncludes(), pcl::io::LZFDepth16ImageReader::read(), pcl::io::LZFRGB24ImageReader::read(), pcl::io::LZFYUV422ImageReader::read(), pcl::io::LZFBayer8ImageReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::io::LZFRGB24ImageReader::readOMP(), pcl::io::LZFYUV422ImageReader::readOMP(), pcl::io::LZFBayer8ImageReader::readOMP(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::SurfaceReconstruction< PointNT >::reconstruct(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::OrganizedConnectedComponentSegmentation< PointT, PointLT >::segment(), pcl::SegmentDifferences< PointT >::segment(), pcl::DisparityMapConverter< PointDEM >::setImage(), pcl::visualization::ImageViewer::showCorrespondences(), pcl::Edge< ImageType, ImageType >::sobelMagnitudeDirection(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::spatialGradient(), pcl::Morphology< PointT >::subtractionBinary(), pcl::PointCloud< pcl::RGB >::swap(), pcl::people::GroundBasedPeopleDetectionApp< PointT >::swapDimensions(), pcl::toPCLPointCloud2(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::track(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::Morphology< PointT >::unionBinary(), pcl::RangeImageBorderExtractor::updatedScoreAccordingToNeighborValues(), pcl::io::vtkPolyDataToPointCloud(), pcl::io::vtkStructuredGridToPointCloud(), and pcl::PCDWriter::writeASCII().

The documentation for this class was generated from the following files:

pcl/common/distances.h
pcl/point_cloud.h

[in]	count	new size of the point cloud
[in]	value	the value to initialize the new points with

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Detailed Description

template<typename PointT> class pcl::PointCloud< PointT >

Member Typedef Documentation

◆ CloudVectorType

◆ const_iterator

◆ const_reference

◆ const_reverse_iterator

◆ ConstPtr

◆ difference_type

◆ iterator

◆ PointType

◆ Ptr

◆ reference

◆ reverse_iterator

◆ size_type

◆ value_type

◆ VectorType

Constructor & Destructor Documentation

◆ PointCloud() [1/3]

◆ PointCloud() [2/3]

◆ PointCloud() [3/3]

Member Function Documentation

◆ assign() [1/3]

◆ assign() [2/3]

◆ assign() [3/3]

◆ at() [1/4]

◆ at() [2/4]

◆ at() [3/4]

◆ at() [4/4]

◆ back() [1/2]

◆ back() [2/2]

◆ begin() [1/2]

◆ begin() [2/2]

◆ cbegin()

◆ cend()

◆ clear()

◆ concatenate() [1/2]

◆ concatenate() [2/2]

◆ crbegin()

◆ crend()

◆ data() [1/2]

◆ data() [2/2]

◆ emplace()

◆ emplace_back()

◆ empty()

◆ end() [1/2]

◆ end() [2/2]

◆ erase() [1/2]

◆ erase() [2/2]

◆ front() [1/2]

◆ front() [2/2]

◆ getMatrixXfMap() [1/4]

◆ getMatrixXfMap() [2/4]

◆ getMatrixXfMap() [3/4]

◆ getMatrixXfMap() [4/4]

◆ insert() [1/3]

◆ insert() [2/3]

◆ insert() [3/3]

◆ isOrganized()

◆ makeShared()

◆ max_size()

◆ operator()() [1/2]

◆ operator()() [2/2]

◆ operator+()

◆ operator+=()

◆ operator[]() [1/2]

◆ operator[]() [2/2]

◆ push_back()

◆ rbegin() [1/2]

◆ rbegin() [2/2]

◆ rend() [1/2]

◆ rend() [2/2]

◆ reserve()

◆ resize() [1/2]

◆ resize() [2/2]

◆ size()

template<typename PointT>
class pcl::PointCloud< PointT >