EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense. More...

#include <pcl/segmentation/extract_clusters.h>

Inheritance diagram for pcl::EuclideanClusterExtraction< PointT >:

Collaboration diagram for pcl::EuclideanClusterExtraction< PointT >:

Public Types
using	PointCloud = pcl::PointCloud<PointT>

using	PointCloudPtr = typename PointCloud::Ptr

using	PointCloudConstPtr = typename PointCloud::ConstPtr

using	KdTree = pcl::search::Search<PointT>

using	KdTreePtr = typename KdTree::Ptr

using	PointIndicesPtr = PointIndices::Ptr

using	PointIndicesConstPtr = PointIndices::ConstPtr

Public Types inherited from pcl::PCLBase< PointT >
using	PointCloud = pcl::PointCloud<PointT>

using	PointCloudPtr = typename PointCloud::Ptr

using	PointCloudConstPtr = typename PointCloud::ConstPtr

using	PointIndicesPtr = PointIndices::Ptr

using	PointIndicesConstPtr = PointIndices::ConstPtr

Public Member Functions
	EuclideanClusterExtraction ()
	Empty constructor.

void	setSearchMethod (const KdTreePtr &tree)
	Provide a pointer to the search object.

KdTreePtr	getSearchMethod () const
	Get a pointer to the search method used.

void	setClusterTolerance (double tolerance)
	Set the spatial cluster tolerance as a measure in the L2 Euclidean space.

double	getClusterTolerance () const
	Get the spatial cluster tolerance as a measure in the L2 Euclidean space.

void	setMinClusterSize (pcl::uindex_t min_cluster_size)
	Set the minimum number of points that a cluster needs to contain in order to be considered valid.

pcl::uindex_t	getMinClusterSize () const
	Get the minimum number of points that a cluster needs to contain in order to be considered valid.

void	setMaxClusterSize (pcl::uindex_t max_cluster_size)
	Set the maximum number of points that a cluster needs to contain in order to be considered valid.

pcl::uindex_t	getMaxClusterSize () const
	Get the maximum number of points that a cluster needs to contain in order to be considered valid.

void	extract (std::vector< PointIndices > &clusters)
	Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>

Public Member Functions inherited from pcl::PCLBase< PointT >
	PCLBase ()
	Empty constructor.

	PCLBase (const PCLBase &base)
	Copy constructor.

virtual	~PCLBase ()=default
	Destructor.

virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset.

PointCloudConstPtr const	getInputCloud () const
	Get a pointer to the input point cloud dataset.

virtual void	setIndices (const IndicesPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.

virtual void	setIndices (const IndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.

virtual void	setIndices (const PointIndicesConstPtr &indices)
	Provide a pointer to the vector of indices that represents the input data.

virtual void	setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols)
	Set the indices for the points laying within an interest region of the point cloud.

IndicesPtr	getIndices ()
	Get a pointer to the vector of indices used.

IndicesConstPtr const	getIndices () const
	Get a pointer to the vector of indices used.

const PointT &	operator[] (std::size_t pos) const
	Override PointCloud operator[] to shorten code.

Protected Member Functions
virtual std::string	getClassName () const
	Class getName method.

bool	initCompute ()
	This method should get called before starting the actual computation.

bool	deinitCompute ()
	This method should get called after finishing the actual computation.

Protected Member Functions inherited from pcl::PCLBase< PointT >
bool	initCompute ()
	This method should get called before starting the actual computation.

bool	deinitCompute ()
	This method should get called after finishing the actual computation.

Protected Attributes
KdTreePtr	tree_
	A pointer to the spatial search object.

double	cluster_tolerance_
	The spatial cluster tolerance as a measure in the L2 Euclidean space.

pcl::uindex_t	min_pts_per_cluster_
	The minimum number of points that a cluster needs to contain in order to be considered valid (default = 1).

pcl::uindex_t	max_pts_per_cluster_
	The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT).

PointCloudConstPtr	input_
	The input point cloud dataset.

IndicesPtr	indices_
	A pointer to the vector of point indices to use.

Protected Attributes inherited from pcl::PCLBase< PointT >
PointCloudConstPtr	input_
	The input point cloud dataset.

IndicesPtr	indices_
	A pointer to the vector of point indices to use.

bool	use_indices_
	Set to true if point indices are used.

bool	fake_indices_
	If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud.

Detailed Description

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

EuclideanClusterExtraction represents a segmentation class for cluster extraction in an Euclidean sense.

Author: Radu Bogdan Rusu

Definition at line 325 of file extract_clusters.h.

Member Typedef Documentation

◆ KdTree

template<typename PointT >

using pcl::EuclideanClusterExtraction< PointT >::KdTree = pcl::search::Search<PointT>

Definition at line 334 of file extract_clusters.h.

◆ KdTreePtr

template<typename PointT >

using pcl::EuclideanClusterExtraction< PointT >::KdTreePtr = typename KdTree::Ptr

Definition at line 335 of file extract_clusters.h.

◆ PointCloud

template<typename PointT >

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

Definition at line 330 of file extract_clusters.h.

◆ PointCloudConstPtr

template<typename PointT >

using pcl::EuclideanClusterExtraction< PointT >::PointCloudConstPtr = typename PointCloud::ConstPtr

Definition at line 332 of file extract_clusters.h.

◆ PointCloudPtr

template<typename PointT >

using pcl::EuclideanClusterExtraction< PointT >::PointCloudPtr = typename PointCloud::Ptr

Definition at line 331 of file extract_clusters.h.

◆ PointIndicesConstPtr

template<typename PointT >

using pcl::EuclideanClusterExtraction< PointT >::PointIndicesConstPtr = PointIndices::ConstPtr

Definition at line 338 of file extract_clusters.h.

◆ PointIndicesPtr

template<typename PointT >

using pcl::EuclideanClusterExtraction< PointT >::PointIndicesPtr = PointIndices::Ptr

Definition at line 337 of file extract_clusters.h.

Constructor & Destructor Documentation

◆ EuclideanClusterExtraction()

template<typename PointT >

pcl::EuclideanClusterExtraction< PointT >::EuclideanClusterExtraction ( )

inline

Empty constructor.

Definition at line 342 of file extract_clusters.h.

Member Function Documentation

◆ deinitCompute()

template<typename PointT >

bool pcl::PCLBase< PointT >::deinitCompute ( )

protected

This method should get called after finishing the actual computation.

Definition at line 173 of file pcl_base.hpp.

◆ extract()

template<typename PointT >

void pcl::EuclideanClusterExtraction< PointT >::extract ( std::vector< PointIndices > & clusters )

Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>

Parameters

[out] clusters the resultant point clusters

Definition at line 228 of file extract_clusters.hpp.

Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute().

◆ getClassName()

template<typename PointT >

virtual std::string pcl::EuclideanClusterExtraction< PointT >::getClassName ( ) const

inlineprotectedvirtual

Class getName method.

Definition at line 440 of file extract_clusters.h.

◆ getClusterTolerance()

template<typename PointT >

double pcl::EuclideanClusterExtraction< PointT >::getClusterTolerance ( ) const

inline

Get the spatial cluster tolerance as a measure in the L2 Euclidean space.

Definition at line 377 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::cluster_tolerance_.

◆ getMaxClusterSize()

template<typename PointT >

pcl::uindex_t pcl::EuclideanClusterExtraction< PointT >::getMaxClusterSize ( ) const

inline

Get the maximum number of points that a cluster needs to contain in order to be considered valid.

Definition at line 409 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::max_pts_per_cluster_.

◆ getMinClusterSize()

template<typename PointT >

pcl::uindex_t pcl::EuclideanClusterExtraction< PointT >::getMinClusterSize ( ) const

inline

Get the minimum number of points that a cluster needs to contain in order to be considered valid.

Definition at line 393 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::min_pts_per_cluster_.

◆ getSearchMethod()

template<typename PointT >

KdTreePtr pcl::EuclideanClusterExtraction< PointT >::getSearchMethod ( ) const

inline

Get a pointer to the search method used.

Todo: fix this for a generic search tree

Definition at line 361 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::tree_.

◆ initCompute()

template<typename PointT >

bool pcl::PCLBase< PointT >::initCompute ( )

protected

This method should get called before starting the actual computation.

Internally, initCompute() does the following:

checks if an input dataset is given, and returns false otherwise
checks whether a set of input indices has been given. Returns true if yes.
if no input indices have been given, a fake set is created, which will be used until:
- either a new set is given via setIndices(), or
- a new cloud is given that has a different set of points. This will trigger an update on the set of fake indices

Definition at line 168 of file pcl_base.hpp.

◆ setClusterTolerance()

template<typename PointT >

void pcl::EuclideanClusterExtraction< PointT >::setClusterTolerance ( double tolerance )

inline

Set the spatial cluster tolerance as a measure in the L2 Euclidean space.

Parameters

[in] tolerance the spatial cluster tolerance as a measure in the L2 Euclidean space

Definition at line 370 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::cluster_tolerance_.

Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute().

◆ setMaxClusterSize()

template<typename PointT >

void pcl::EuclideanClusterExtraction< PointT >::setMaxClusterSize ( pcl::uindex_t max_cluster_size )

inline

Set the maximum number of points that a cluster needs to contain in order to be considered valid.

Parameters

[in] max_cluster_size the maximum cluster size

Definition at line 402 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::max_pts_per_cluster_.

Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute().

◆ setMinClusterSize()

template<typename PointT >

void pcl::EuclideanClusterExtraction< PointT >::setMinClusterSize ( pcl::uindex_t min_cluster_size )

inline

Set the minimum number of points that a cluster needs to contain in order to be considered valid.

Parameters

[in] min_cluster_size the minimum cluster size

Definition at line 386 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::min_pts_per_cluster_.

Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute().

◆ setSearchMethod()

template<typename PointT >

void pcl::EuclideanClusterExtraction< PointT >::setSearchMethod ( const KdTreePtr & tree )

inline

Provide a pointer to the search object.

Parameters

[in] tree a pointer to the spatial search object.

Definition at line 352 of file extract_clusters.h.

References pcl::EuclideanClusterExtraction< PointT >::tree_.

Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute().

Member Data Documentation

◆ cluster_tolerance_

template<typename PointT >

double pcl::EuclideanClusterExtraction< PointT >::cluster_tolerance_

protected

The spatial cluster tolerance as a measure in the L2 Euclidean space.

Definition at line 431 of file extract_clusters.h.

Referenced by pcl::EuclideanClusterExtraction< PointT >::getClusterTolerance(), and pcl::EuclideanClusterExtraction< PointT >::setClusterTolerance().

◆ indices_

template<typename PointT >

IndicesPtr pcl::PCLBase< PointT >::indices_

protected

A pointer to the vector of point indices to use.

Definition at line 150 of file pcl_base.h.

◆ input_

template<typename PointT >

PointCloudConstPtr pcl::PCLBase< PointT >::input_

protected

The input point cloud dataset.

Definition at line 147 of file pcl_base.h.

◆ max_pts_per_cluster_

template<typename PointT >

pcl::uindex_t pcl::EuclideanClusterExtraction< PointT >::max_pts_per_cluster_

protected

The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT).

Definition at line 437 of file extract_clusters.h.

Referenced by pcl::EuclideanClusterExtraction< PointT >::getMaxClusterSize(), and pcl::EuclideanClusterExtraction< PointT >::setMaxClusterSize().

◆ min_pts_per_cluster_

template<typename PointT >

pcl::uindex_t pcl::EuclideanClusterExtraction< PointT >::min_pts_per_cluster_

protected

The minimum number of points that a cluster needs to contain in order to be considered valid (default = 1).

Definition at line 434 of file extract_clusters.h.

Referenced by pcl::EuclideanClusterExtraction< PointT >::getMinClusterSize(), and pcl::EuclideanClusterExtraction< PointT >::setMinClusterSize().

◆ tree_

template<typename PointT >

KdTreePtr pcl::EuclideanClusterExtraction< PointT >::tree_

protected

A pointer to the spatial search object.

Definition at line 428 of file extract_clusters.h.

Referenced by pcl::EuclideanClusterExtraction< PointT >::getSearchMethod(), and pcl::EuclideanClusterExtraction< PointT >::setSearchMethod().

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

pcl/segmentation/extract_clusters.h
pcl/segmentation/impl/extract_clusters.hpp

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ KdTree

◆ KdTreePtr

◆ PointCloud

◆ PointCloudConstPtr

◆ PointCloudPtr

◆ PointIndicesConstPtr

◆ PointIndicesPtr

Constructor & Destructor Documentation

◆ EuclideanClusterExtraction()

Member Function Documentation

◆ deinitCompute()

◆ extract()

◆ getClassName()

◆ getClusterTolerance()

◆ getMaxClusterSize()

◆ getMinClusterSize()

◆ getSearchMethod()

◆ initCompute()

◆ setClusterTolerance()

◆ setMaxClusterSize()

◆ setMinClusterSize()

◆ setSearchMethod()

Member Data Documentation

◆ cluster_tolerance_

◆ indices_

◆ input_

◆ max_pts_per_cluster_

◆ min_pts_per_cluster_

◆ tree_