pcl::EuclideanClusterExtraction< PointT > Class Template Reference

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

#include <extract_clusters.h>

Inheritance diagram for pcl::EuclideanClusterExtraction< PointT >:

Public Types
typedef pcl::KdTree< PointT >	KdTree
typedef pcl::KdTree< PointT >::Ptr	KdTreePtr
typedef pcl::PointCloud< PointT >	PointCloud
typedef PointCloud::ConstPtr	PointCloudConstPtr
typedef PointCloud::Ptr	PointCloudPtr
typedef PointIndices::ConstPtr	PointIndicesConstPtr
typedef PointIndices::Ptr	PointIndicesPtr
Public Member Functions
	EuclideanClusterExtraction ()
	Empty constructor.
void	extract (std::vector< PointIndices > &clusters)
	Cluster extraction in a PointCloud given by <setInputCloud (), setIndices ()>
double	getClusterTolerance ()
	Get the spatial cluster tolerance as a measure in the L2 Euclidean space.
int	getMaxClusterSize ()
	Get the maximum number of points that a cluster needs to contain in order to be considered valid.
int	getMinClusterSize ()
	Get the minimum number of points that a cluster needs to contain in order to be considered valid.
KdTreePtr	getSearchMethod ()
	Get a pointer to the search method used.
int	getSpatialLocator ()
	Get the spatial locator type used.
void	setClusterTolerance (double tolerance)
	Set the spatial cluster tolerance as a measure in the L2 Euclidean space.
void	setMaxClusterSize (int max_cluster_size)
	Set the maximum number of points that a cluster needs to contain in order to be considered valid.
void	setMinClusterSize (int min_cluster_size)
	Set the minimum number of points that a cluster needs to contain in order to be considered valid.
void	setSearchMethod (const KdTreePtr &tree)
	Provide a pointer to the search object.
void	setSpatialLocator (int locator)
	Set the spatial locator type to use.
Protected Member Functions
virtual std::string	getClassName () const
	Class getName method.
Protected Attributes
double	cluster_tolerance_
	The spatial cluster tolerance as a measure in the L2 Euclidean space.
int	max_pts_per_cluster_
	The maximum number of points that a cluster needs to contain in order to be considered valid (default = MAXINT).
int	min_pts_per_cluster_
	The minimum number of points that a cluster needs to contain in order to be considered valid (default = 1).
int	spatial_locator_
	Parameter for the spatial locator tree. By convention, the values represent: 0: ANN (Approximate Nearest Neigbor library) kd-tree 1: FLANN (Fast Library for Approximate Nearest Neighbors) kd-tree 2: Organized spatial dataset index.
KdTreePtr	tree_
	A pointer to the spatial search object.
Private Types
typedef PCLBase< PointT >	BasePCLBase

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 279 of file extract_clusters.h.

Member Typedef Documentation

template<typename PointT >

typedef PCLBase<PointT> pcl::EuclideanClusterExtraction< PointT >::BasePCLBase [private]

Definition at line 281 of file extract_clusters.h.

template<typename PointT >

typedef pcl::KdTree<PointT> pcl::EuclideanClusterExtraction< PointT >::KdTree

Definition at line 288 of file extract_clusters.h.

template<typename PointT >

typedef pcl::KdTree<PointT>::Ptr pcl::EuclideanClusterExtraction< PointT >::KdTreePtr

Definition at line 289 of file extract_clusters.h.

template<typename PointT >

typedef pcl::PointCloud<PointT> pcl::EuclideanClusterExtraction< PointT >::PointCloud

Reimplemented from pcl::PCLBase< PointT >.

Definition at line 284 of file extract_clusters.h.

template<typename PointT >

typedef PointCloud::ConstPtr pcl::EuclideanClusterExtraction< PointT >::PointCloudConstPtr

Reimplemented from pcl::PCLBase< PointT >.

Definition at line 286 of file extract_clusters.h.

template<typename PointT >

typedef PointCloud::Ptr pcl::EuclideanClusterExtraction< PointT >::PointCloudPtr

Reimplemented from pcl::PCLBase< PointT >.

Definition at line 285 of file extract_clusters.h.

template<typename PointT >

typedef PointIndices::ConstPtr pcl::EuclideanClusterExtraction< PointT >::PointIndicesConstPtr

Reimplemented from pcl::PCLBase< PointT >.

Definition at line 292 of file extract_clusters.h.

template<typename PointT >

typedef PointIndices::Ptr pcl::EuclideanClusterExtraction< PointT >::PointIndicesPtr

Reimplemented from pcl::PCLBase< PointT >.

Definition at line 291 of file extract_clusters.h.

Constructor & Destructor Documentation

template<typename PointT >

pcl::EuclideanClusterExtraction< PointT >::EuclideanClusterExtraction ( ) [inline]

Empty constructor.

Definition at line 296 of file extract_clusters.h.

Member Function Documentation

template<typename PointT >

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

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

Parameters:

clusters

the resultant point clusters

Definition at line 197 of file extract_clusters.hpp.

template<typename PointT >

virtual std::string pcl::EuclideanClusterExtraction< PointT >::getClassName ( ) const [inline, protected, virtual]

Class getName method.

Definition at line 370 of file extract_clusters.h.

template<typename PointT >

double pcl::EuclideanClusterExtraction< PointT >::getClusterTolerance ( ) [inline]

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

Definition at line 314 of file extract_clusters.h.

template<typename PointT >

int pcl::EuclideanClusterExtraction< PointT >::getMaxClusterSize ( ) [inline]

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

Definition at line 330 of file extract_clusters.h.

template<typename PointT >

int pcl::EuclideanClusterExtraction< PointT >::getMinClusterSize ( ) [inline]

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

Definition at line 322 of file extract_clusters.h.

template<typename PointT >

KdTreePtr pcl::EuclideanClusterExtraction< PointT >::getSearchMethod ( ) [inline]

Get a pointer to the search method used.

Definition at line 306 of file extract_clusters.h.

template<typename PointT >

int pcl::EuclideanClusterExtraction< PointT >::getSpatialLocator ( ) [inline]

Get the spatial locator type used.

Definition at line 342 of file extract_clusters.h.

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:

tolerance

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

Definition at line 311 of file extract_clusters.h.

template<typename PointT >

void pcl::EuclideanClusterExtraction< PointT >::setMaxClusterSize ( int max_cluster_size ) [inline]

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

Parameters:

max_cluster_size

the maximum cluster size

Definition at line 327 of file extract_clusters.h.

template<typename PointT >

void pcl::EuclideanClusterExtraction< PointT >::setMinClusterSize ( int min_cluster_size ) [inline]

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

Parameters:

min_cluster_size

the minimum cluster size

Definition at line 319 of file extract_clusters.h.

template<typename PointT >

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

Provide a pointer to the search object.

Parameters:

tree

a pointer to the spatial search object.

Definition at line 303 of file extract_clusters.h.

template<typename PointT >

void pcl::EuclideanClusterExtraction< PointT >::setSpatialLocator ( int locator ) [inline]

Set the spatial locator type to use.

Parameters:

locator

the spatial locator type

Definition at line 340 of file extract_clusters.h.

Member Data Documentation

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 361 of file extract_clusters.h.

template<typename PointT >

int 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 367 of file extract_clusters.h.

template<typename PointT >

int 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 364 of file extract_clusters.h.

template<typename PointT >

int pcl::EuclideanClusterExtraction< PointT >::spatial_locator_ [protected]

Parameter for the spatial locator tree. By convention, the values represent: 0: ANN (Approximate Nearest Neigbor library) kd-tree 1: FLANN (Fast Library for Approximate Nearest Neighbors) kd-tree 2: Organized spatial dataset index.

Definition at line 358 of file extract_clusters.h.

template<typename PointT >

KdTreePtr pcl::EuclideanClusterExtraction< PointT >::tree_ [protected]

A pointer to the spatial search object.

Definition at line 351 of file extract_clusters.h.

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

pcl::EuclideanClusterExtraction< PointT > Class Template Reference

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Private Types

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

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