Point Cloud Library (PCL)  1.11.1-dev
List of all members | Public Types | Public Member Functions | Static Public Member Functions | Public Attributes
pcl::PointCloud< PointT > Class Template Reference

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...
 
PointCloudoperator+= (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 PointTat (int column, int row) const
 Obtain the point given by the (column, row) coordinates. More...
 
PointTat (int column, int row)
 Obtain the point given by the (column, row) coordinates. More...
 
const PointToperator() (std::size_t column, std::size_t row) const
 Obtain the point given by the (column, row) coordinates. More...
 
PointToperator() (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
 
PointTdata () noexcept
 
const PointTdata () 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 PointToperator[] (std::size_t n) const
 
PointToperator[] (std::size_t n)
 
const PointTat (std::size_t n) const
 
PointTat (std::size_t n)
 
const PointTfront () const
 
PointTfront ()
 
const PointTback () const
 
PointTback ()
 
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:

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:

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]pcthe cloud to copy into this
[in]indicesthe 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]columnthe column coordinate
[in]rowthe 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]columnthe column coordinate
[in]rowthe 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

◆ 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

◆ cbegin()

template<typename PointT >
const_iterator pcl::PointCloud< PointT >::cbegin ( ) const
inlinenoexcept

◆ cend()

template<typename PointT >
const_iterator pcl::PointCloud< PointT >::cend ( ) const
inlinenoexcept

◆ 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]positioniterator before which the point will be emplaced
[in]argsthe 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]argsthe 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

◆ 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

◆ 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]firstwhere to start erasing points from
[in]lastwhere 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]positionwhat 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

◆ 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]dimthe number of dimensions to consider for each point
[in]stridethe number of values in each point (will be the number of values that separate two of the columns)
[in]offsetthe 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]dimthe number of dimensions to consider for each point
[in]stridethe number of values in each point (will be the number of values that separate two of the columns)
[in]offsetthe 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]positionwhere to insert the point
[in]ptthe 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]positionwhere to insert the data
[in]firstwhere to start inserting the points from
[in]lastwhere 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]positionwhere to insert the point
[in]nthe number of times to insert the point
[in]ptthe point to insert

Definition at line 586 of file point_cloud.h.

◆ isOrganized()

template<typename PointT >
bool pcl::PointCloud< PointT >::isOrganized ( ) const
inline

◆ 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]columnthe column coordinate
[in]rowthe 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]columnthe column coordinate
[in]rowthe 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]rhsthe 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]rhsthe 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]ptthe 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

◆ 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]countnew size of the point cloud
    [in]valuethe 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]countnew 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.

Referenced by pcl::visualization::PCLHistogramVisualizer::addFeatureHistogram(), pcl::visualization::PCLPlotter::addFeatureHistogram(), pcl::visualization::ImageViewer::addMask(), pcl::visualization::PCLVisualizer::addPointCloudIntensityGradients(), pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::PCLVisualizer::addPointCloudPrincipalCurvatures(), pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::visualization::ImageViewer::addRectangle(), pcl::LineRGBD< PointXYZT, PointRGBT >::addTemplate(), pcl::recognition::TrimmedICP< pcl::PointXYZ, float >::align(), pcl::ShadowPoints< PointT, NormalT >::applyFilter(), pcl::UniformSampling< PointT >::applyFilter(), pcl::SamplingSurfaceNormal< PointT >::applyFilter(), pcl::ApproximateVoxelGrid< PointT >::applyFilter(), pcl::VoxelGrid< pcl::PointXYZRGBL >::applyFilter(), pcl::VoxelGridCovariance< PointTarget >::applyFilter(), pcl::applyMorphologicalOperator(), pcl::approximatePolygon(), pcl::approximatePolygon2D(), pcl::UnaryClassifier< PointT >::assignLabels(), pcl::calculatePolygonArea(), pcl::PlaneClipper3D< PointT >::clipPointCloud3D(), pcl::BoxClipper3D< PointT >::clipPointCloud3D(), pcl::BRISK2DEstimation< PointInT, PointOutT, KeypointT, IntensityT >::compute(), pcl::Feature< PointInT, pcl::SHOT352 >::compute(), pcl::features::computeApproximateCovariances(), pcl::features::computeApproximateNormals(), pcl::computeCovarianceMatrix(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::computeCovariances(), pcl::ESFEstimation< PointInT, PointOutT >::computeESF(), pcl::GRSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::computeFeature(), pcl::RSDEstimation< PointInT, PointNT, PointOutT >::computeFeature(), pcl::computeMeanAndCovarianceMatrix(), pcl::computePointNormal(), 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 >::convertTsdfVectors(), pcl::copyPointCloud(), pcl::LineRGBD< PointXYZT, PointRGBT >::createAndAddTemplate(), pcl::visualization::createPolygon(), pcl::demeanPointCloud(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::derivatives(), pcl::Edge< ImageType, ImageType >::detectEdgePrewitt(), pcl::Edge< ImageType, ImageType >::detectEdgeRoberts(), pcl::Edge< ImageType, ImageType >::detectEdgeSobel(), pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::SIFTKeypoint< PointInT, PointOutT >::detectKeypoints(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::SUSANKeypoint< PointInT, PointOutT, NormalT, IntensityT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::registration::TransformationEstimationDualQuaternion< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimation2D< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationDQ< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationSymmetricPointToPlaneLLS< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationPointToPlaneLLS< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationPointToPlaneLLSWeighted< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationSVD< PointT, PointT, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimation3Point< PointSource, PointTarget, Scalar >::estimateRigidTransformation(), pcl::registration::TransformationEstimationLM< PointSource, PointTarget, float >::estimateRigidTransformation(), pcl::registration::TransformationEstimationPointToPlaneWeighted< PointSource, PointTarget, MatScalar >::estimateRigidTransformation(), pcl::io::PointCloudImageExtractor< PointT >::extract(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::extractDescriptors(), pcl::gpu::extractEuclideanClusters(), pcl::extractEuclideanClusters(), pcl::io::PointCloudImageExtractorWithScaling< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromNormalField< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromRGBField< PointT >::extractImpl(), pcl::io::PointCloudImageExtractorFromLabelField< PointT >::extractImpl(), pcl::gpu::extractLabeledEuclideanClusters(), pcl::extractLabeledEuclideanClusters(), pcl::occlusion_reasoning::ZBuffering< ModelT, SceneT >::filter(), pcl::occlusion_reasoning::filter(), pcl::CVFHEstimation< PointInT, PointNT, PointOutT >::filterNormalsWithHighCurvature(), pcl::OURCVFHEstimation< PointInT, PointNT, PointOutT >::filterNormalsWithHighCurvature(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::findObjects(), pcl::PCDWriter::generateHeader(), pcl::getApproximateIndices(), pcl::UnaryClassifier< PointT >::getCloudWithLabel(), pcl::features::ISMVoteList< PointT >::getColoredCloud(), pcl::getMaxDistance(), pcl::getMaxSegment(), pcl::getMeanPointDensity(), pcl::occlusion_reasoning::getOccludedCloud(), pcl::getPointCloudDifference(), pcl::getPointsInBox(), pcl::outofcore::OutofcoreOctreeDiskContainer< PointT >::insertRange(), pcl::Morphology< PointT >::intersectionBinary(), pcl::isPointIn2DPolygon(), pcl::isXYPointIn2DXYPolygon(), pcl::UnaryClassifier< PointT >::kmeansClustering(), pcl::LineRGBD< PointXYZT, PointRGBT >::loadTemplates(), pcl::KdTree< FeatureT >::nearestKSearch(), pcl::search::Search< PointXYZRGB >::nearestKSearch(), pcl::VoxelGridCovariance< PointTarget >::nearestKSearch(), pcl::search::Search< PointXYZRGB >::nearestKSearchT(), pcl::operator<<(), pcl::MovingLeastSquares< PointInT, PointOutT >::performProcessing(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::MarchingCubes< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::ConvexHull< PointInT >::performReconstruction3D(), pcl::PointCloud< pcl::RGB >::PointCloud(), pcl::io::pointCloudTovtkPolyData(), pcl::MovingLeastSquares< PointInT, PointOutT >::process(), pcl::SampleConsensusModelLine< PointT >::projectPoints(), pcl::SampleConsensusModelStick< PointT >::projectPoints(), pcl::SampleConsensusModelCircle2D< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelCircle3D< pcl::PointXYZRGB >::projectPoints(), pcl::SampleConsensusModelCylinder< pcl::PointXYZRGB, PointNT >::projectPoints(), pcl::SampleConsensusModelCone< pcl::PointXYZRGB, PointNT >::projectPoints(), pcl::UnaryClassifier< PointT >::queryFeatureDistances(), pcl::KdTree< FeatureT >::radiusSearch(), pcl::search::Search< PointXYZRGB >::radiusSearch(), pcl::VoxelGridCovariance< PointTarget >::radiusSearch(), pcl::search::Search< PointXYZRGB >::radiusSearchT(), pcl::io::LZFRGB24ImageReader::read(), pcl::io::LZFBayer8ImageReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::io::LZFRGB24ImageReader::readOMP(), pcl::io::LZFBayer8ImageReader::readOMP(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::seededHueSegmentation(), pcl::ExtractPolygonalPrismData< PointT >::segment(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setEdgeDataCloud(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setFaceDataCloud(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setHalfEdgeDataCloud(), pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget >::setInputSource(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::setPointsToTrack(), pcl::poisson::Octree< Degree >::setTree(), pcl::geometry::MeshBase< QuadMesh< MeshTraitsT >, MeshTraitsT, QuadMeshTag >::setVertexDataCloud(), pcl::ism::ImplicitShapeModelEstimation< FeatureSize, PointT, NormalT >::simplifyCloud(), pcl::Edge< ImageType, ImageType >::sobelMagnitudeDirection(), pcl::Morphology< PointT >::subtractionBinary(), pcl::toPCLPointCloud2(), pcl::tracking::PyramidalKLTTracker< PointInT, IntensityT >::track(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::Morphology< PointT >::unionBinary(), pcl::visualization::PCLHistogramVisualizer::updateFeatureHistogram(), pcl::visualization::PCLVisualizer::updatePointCloud(), pcl::visualization::PCLVisualizer::updatePolygonMesh(), pcl::registration::KFPCSInitialAlignment< PointSource, PointTarget, NormalT, Scalar >::validateTransformation(), pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::validateTransformation(), pcl::io::vtkPolyDataToPointCloud(), pcl::PCDWriter::writeASCII(), pcl::PCDWriter::writeBinary(), and pcl::PCDWriter::writeBinaryCompressed().

◆ swap()

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

Swap a point cloud with another cloud.

Parameters
[in,out]rhspoint 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.

Referenced by pcl::visualization::ImageViewer::addMask(), pcl::visualization::PCLVisualizer::addPointCloudNormals(), pcl::visualization::ImageViewer::addRectangle(), pcl::visualization::ImageViewer::addRGBImage(), pcl::Registration< PointSource, PointTarget >::align(), pcl::LocalMaximum< PointT >::applyFilter(), pcl::MedianFilter< PointT >::applyFilter(), pcl::ShadowPoints< PointT, NormalT >::applyFilter(), pcl::GridMinimum< PointT >::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::Edge< ImageType, ImageType >::canny(), 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::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::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::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::visualization::ImageViewer::showCorrespondences(), pcl::Edge< ImageType, ImageType >::sobelMagnitudeDirection(), 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::io::vtkPolyDataToPointCloud(), pcl::io::vtkStructuredGridToPointCloud(), and pcl::PCDWriter::writeASCII().

◆ 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.

Referenced by pcl::visualization::PCLVisualizer::addPolygonMesh(), pcl::Registration< PointSource, PointTarget >::align(), pcl::LocalMaximum< PointT >::applyFilter(), pcl::GridMinimum< PointT >::applyFilter(), pcl::ExtractIndices< PointT >::applyFilter(), pcl::UniformSampling< PointT >::applyFilter(), pcl::FilterIndices< PointInT >::applyFilter(), pcl::ApproximateVoxelGrid< PointT >::applyFilter(), pcl::VoxelGrid< pcl::PointXYZRGBL >::applyFilter(), pcl::VoxelGridCovariance< PointTarget >::applyFilter(), pcl::ConditionalRemoval< PointT >::applyFilter(), pcl::GFPFHEstimation< PointInT, PointLT, PointOutT >::compute(), pcl::BRISK2DEstimation< PointInT, PointOutT, KeypointT, IntensityT >::compute(), pcl::GASDEstimation< PointInT, GASDSignature984 >::compute(), pcl::Feature< PointInT, pcl::SHOT352 >::compute(), pcl::compute3DCentroid(), pcl::computeCentroid(), pcl::computeCovarianceMatrix(), pcl::IntensityGradientEstimation< PointInT, PointNT, PointOutT, IntensitySelectorT >::computeFeature(), pcl::SHOTLocalReferenceFrameEstimation< PointInT, ReferenceFrame >::computeFeature(), pcl::MomentInvariantsEstimation< PointInT, PointOutT >::computeFeature(), pcl::IntensitySpinEstimation< PointInT, PointOutT >::computeFeature(), pcl::SHOTEstimation< PointInT, PointNT, pcl::SHOT352, pcl::ReferenceFrame >::computeFeature(), pcl::SHOTColorEstimation< PointInT, PointNT, pcl::SHOT1344, pcl::ReferenceFrame >::computeFeature(), pcl::NormalEstimation< PointInT, PointNT >::computeFeature(), pcl::IntegralImageNormalEstimation< pcl::PointXYZRGBA, pcl::Normal >::computeFeatureFull(), pcl::IntegralImageNormalEstimation< pcl::PointXYZRGBA, pcl::Normal >::computeFeaturePart(), pcl::computeMeanAndCovarianceMatrix(), pcl::PointCloud< pcl::RGB >::concatenate(), pcl::concatenateFields(), pcl::io::OrganizedConversion< PointT, false >::convert(), pcl::io::OrganizedConversion< PointT, true >::convert(), pcl::UnaryClassifier< PointT >::convertCloud(), pcl::filters::Convolution3D< PointIn, PointOut, KernelT >::convolve(), pcl::copyPointCloud(), pcl::demeanPointCloud(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::HarrisKeypoint3D< PointInT, PointOutT, NormalT >::detectKeypoints(), pcl::MultiscaleFeaturePersistence< PointSource, PointFeature >::determinePersistentFeatures(), pcl::common::CloudGenerator< PointT, GeneratorT >::fill(), pcl::common::CloudGenerator< pcl::PointXY, GeneratorT >::fill(), pcl::fromPCLPointCloud2(), pcl::UnaryClassifier< PointT >::getCloudWithLabel(), pcl::MinCutSegmentation< PointT >::getColoredCloud(), pcl::RegionGrowing< PointT, pcl::Normal >::getColoredCloud(), pcl::RegionGrowing< PointT, pcl::Normal >::getColoredCloudRGBA(), pcl::getMaxDistance(), pcl::getMinMax3D(), pcl::getPointCloudDifference(), pcl::getPointsInBox(), pcl::filters::Convolution< PointIn, PointOut >::initCompute(), pcl::UnaryClassifier< PointT >::kmeansClustering(), pcl::operator<<(), pcl::ConcaveHull< PointInT >::performReconstruction(), pcl::GridProjection< PointNT >::performReconstruction(), pcl::ConvexHull< PointInT >::performReconstruction2D(), pcl::ConvexHull< PointInT >::performReconstruction3D(), pcl::io::pointCloudTovtkPolyData(), 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::io::LZFDepth16ImageReader::read(), pcl::io::LZFDepth16ImageReader::readOMP(), pcl::ConcaveHull< PointInT >::reconstruct(), pcl::ConvexHull< PointInT >::reconstruct(), pcl::removeNaNFromPointCloud(), pcl::removeNaNNormalsFromPointCloud(), pcl::PointCloud< pcl::RGB >::swap(), pcl::toPCLPointCloud2(), pcl::transformPointCloud(), pcl::transformPointCloudWithNormals(), pcl::visualization::PCLVisualizer::updatePointCloud(), pcl::visualization::PCLVisualizer::updatePolygonMesh(), pcl::io::vtkPolyDataToPointCloud(), and pcl::io::vtkStructuredGridToPointCloud().

◆ 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_origin_

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

◆ 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::PointCloud< pcl::PointXYZ >
pcl::PointXYZ
A point structure representing Euclidean xyz coordinates.
Definition: point_types.hpp:300
pcl::PointCloud::push_back
void push_back(const PointT &pt)
Insert a new point in the cloud, at the end of the container.
Definition: point_cloud.h:543