Generic search class. More...

#include <pcl/search/search.h>

Inheritance diagram for pcl::search::Search< PointT >:

Public Types
using	PointCloud = pcl::PointCloud<PointT>
using	PointCloudPtr = typename PointCloud::Ptr
using	PointCloudConstPtr = typename PointCloud::ConstPtr
using	Ptr = shared_ptr<pcl::search::Search<PointT> >
using	ConstPtr = shared_ptr<const pcl::search::Search<PointT> >
using	IndicesPtr = pcl::IndicesPtr
using	IndicesConstPtr = pcl::IndicesConstPtr

Public Member Functions
	Search (const std::string &name="", bool sorted=false)
	Constructor.
virtual	~Search ()=default
	Destructor.
virtual const std::string &	getName () const
	Returns the search method name.
virtual void	setSortedResults (bool sorted)
	sets whether the results should be sorted (ascending in the distance) or not
virtual bool	getSortedResults ()
	Gets whether the results should be sorted (ascending in the distance) or not Otherwise the results may be returned in any order.
virtual bool	setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices=IndicesConstPtr())
	Pass the input dataset that the search will be performed on.
virtual PointCloudConstPtr	getInputCloud () const
	Get a pointer to the input point cloud dataset.
virtual IndicesConstPtr	getIndices () const
	Get a pointer to the vector of indices used.
virtual int	nearestKSearch (const PointT &point, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const =0
	Search for the k-nearest neighbors for the given query point.
template<typename PointTDiff>
int	nearestKSearchT (const PointTDiff &point, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const
	Search for k-nearest neighbors for the given query point.
virtual int	nearestKSearch (const PointCloud &cloud, index_t index, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const
	Search for k-nearest neighbors for the given query point.
virtual int	nearestKSearch (index_t index, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const
	Search for k-nearest neighbors for the given query point (zero-copy).
virtual void	nearestKSearch (const PointCloud &cloud, const Indices &indices, int k, std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances) const
	Search for the k-nearest neighbors for the given query point.
template<typename PointTDiff>
void	nearestKSearchT (const pcl::PointCloud< PointTDiff > &cloud, const Indices &indices, int k, std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances) const
	Search for the k-nearest neighbors for the given query point.
virtual int	radiusSearch (const PointT &point, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const =0
	Search for all the nearest neighbors of the query point in a given radius.
template<typename PointTDiff>
int	radiusSearchT (const PointTDiff &point, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const
	Search for all the nearest neighbors of the query point in a given radius.
virtual int	radiusSearch (const PointCloud &cloud, index_t index, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const
	Search for all the nearest neighbors of the query point in a given radius.
virtual int	radiusSearch (index_t index, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const
	Search for all the nearest neighbors of the query point in a given radius (zero-copy).
virtual void	radiusSearch (const PointCloud &cloud, const Indices &indices, double radius, std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances, unsigned int max_nn=0) const
	Search for all the nearest neighbors of the query point in a given radius.
template<typename PointTDiff>
void	radiusSearchT (const pcl::PointCloud< PointTDiff > &cloud, const Indices &indices, double radius, std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances, unsigned int max_nn=0) const
	Search for all the nearest neighbors of the query points in a given radius.

Protected Member Functions
void	sortResults (Indices &indices, std::vector< float > &distances) const

Protected Attributes
PointCloudConstPtr	input_
IndicesConstPtr	indices_
bool	sorted_results_
std::string	name_

Detailed Description

template<typename PointT>
class pcl::search::Search< PointT >

Generic search class.

All search wrappers must inherit from this.

Each search method must implement 2 different types of search:

nearestKSearch - search for K-nearest neighbors.
radiusSearch - search for all nearest neighbors in a sphere of a given radius

The input to each search method can be given in 3 different ways:

as a query point
as a (cloud, index) pair
as an index

For the latter option, it is assumed that the user specified the input via a setInputCloud () method first.

Note: In case of an error, all methods are supposed to return 0 as the number of neighbors found.; libpcl_search deals with three-dimensional search problems. For higher level dimensional search, please refer to the libpcl_kdtree module.

Author: Radu B. Rusu

Definition at line 74 of file search.h.

Member Typedef Documentation

◆ ConstPtr

template<typename PointT>

using pcl::search::Search< PointT >::ConstPtr = shared_ptr<const pcl::search::Search<PointT> >

Definition at line 82 of file search.h.

◆ IndicesConstPtr

template<typename PointT>

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

Definition at line 85 of file search.h.

◆ IndicesPtr

template<typename PointT>

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

Definition at line 84 of file search.h.

◆ PointCloud

template<typename PointT>

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

Definition at line 77 of file search.h.

◆ PointCloudConstPtr

template<typename PointT>

using pcl::search::Search< PointT >::PointCloudConstPtr = typename PointCloud::ConstPtr

Definition at line 79 of file search.h.

◆ PointCloudPtr

template<typename PointT>

using pcl::search::Search< PointT >::PointCloudPtr = typename PointCloud::Ptr

Definition at line 78 of file search.h.

◆ Ptr

template<typename PointT>

using pcl::search::Search< PointT >::Ptr = shared_ptr<pcl::search::Search<PointT> >

Definition at line 81 of file search.h.

Constructor & Destructor Documentation

◆ Search()

template<typename PointT>

pcl::search::Search< PointT >::Search	(	const std::string &	name = "",
		bool	sorted = false )

Constructor.

Definition at line 45 of file search.hpp.

References input_, name_, and sorted_results_.

Referenced by pcl::search::BruteForce< PointT >::BruteForce(), pcl::search::FlannSearch< PointT, FlannDistance >::FlannSearch(), pcl::search::KdTree< PointT, Tree >::KdTree(), pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::Octree(), and pcl::search::OrganizedNeighbor< PointT >::OrganizedNeighbor().

◆ ~Search()

template<typename PointT>

virtual pcl::search::Search< PointT >::~Search ( )

virtualdefault

Destructor.

Member Function Documentation

◆ getIndices()

template<typename PointT>

virtual IndicesConstPtr pcl::search::Search< PointT >::getIndices ( ) const

inlinevirtual

Get a pointer to the vector of indices used.

Definition at line 131 of file search.h.

Referenced by pcl::extractEuclideanClusters().

◆ getInputCloud()

template<typename PointT>

virtual PointCloudConstPtr pcl::search::Search< PointT >::getInputCloud ( ) const

inlinevirtual

Get a pointer to the input point cloud dataset.

Definition at line 124 of file search.h.

Referenced by pcl::extractEuclideanClusters(), pcl::extractEuclideanClusters(), pcl::extractLabeledEuclideanClusters(), pcl::seededHueSegmentation(), and pcl::seededHueSegmentation().

◆ getName()

template<typename PointT>

const std::string & pcl::search::Search< PointT >::getName ( ) const

virtual

Returns the search method name.

Definition at line 54 of file search.hpp.

References name_.

Referenced by pcl::search::OrganizedNeighbor< PointT >::estimateProjectionMatrix().

◆ getSortedResults()

template<typename PointT>

bool pcl::search::Search< PointT >::getSortedResults ( )

virtual

Gets whether the results should be sorted (ascending in the distance) or not Otherwise the results may be returned in any order.

Definition at line 68 of file search.hpp.

References sorted_results_.

Referenced by pcl::extractEuclideanClusters(), pcl::extractEuclideanClusters(), pcl::extractLabeledEuclideanClusters(), pcl::seededHueSegmentation(), and pcl::seededHueSegmentation().

◆ nearestKSearch() [1/4]

template<typename PointT>

void pcl::search::Search< PointT >::nearestKSearch	(	const PointCloud &	cloud,
		const Indices &	indices,
		int	k,
		std::vector< Indices > &	k_indices,
		std::vector< std::vector< float > > &	k_sqr_distances ) const

virtual

Search for the k-nearest neighbors for the given query point.

Parameters

[in]	cloud	the point cloud data
[in]	indices	a vector of point cloud indices to query for nearest neighbors
[in]	k	the number of neighbors to search for
[out]	k_indices	the resultant indices of the neighboring points, k_indices[i] corresponds to the neighbors of the query point i
[out]	k_sqr_distances	the resultant squared distances to the neighboring points, k_sqr_distances[i] corresponds to the neighbors of the query point i

Reimplemented in pcl::search::FlannSearch< PointT, FlannDistance >.

Definition at line 114 of file search.hpp.

◆ nearestKSearch() [2/4]

template<typename PointT>

int pcl::search::Search< PointT >::nearestKSearch	(	const PointCloud &	cloud,
		index_t	index,
		int	k,
		Indices &	k_indices,
		std::vector< float > &	k_sqr_distances ) const

virtual

Search for k-nearest neighbors for the given query point.

Attention: This method does not do any bounds checking for the input index (i.e., index >= cloud.size () || index < 0), and assumes valid (i.e., finite) data.

Parameters

[in]	cloud	the point cloud data
[in]	index	a valid index in cloud representing a valid (i.e., finite) query point
[in]	k	the number of neighbors to search for
[out]	k_indices	the resultant indices of the neighboring points (must be resized to k a priori!)
[out]	k_sqr_distances	the resultant squared distances to the neighboring points (must be resized to k a priori!)

Returns: number of neighbors found

Exceptions

asserts in debug mode if the index is not between 0 and the maximum number of points

Reimplemented in pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, and pcl::search::Octree< PointInT >.

Definition at line 86 of file search.hpp.

◆ nearestKSearch() [3/4]

template<typename PointT>

virtual int pcl::search::Search< PointT >::nearestKSearch	(	const PointT &	point,
		int	k,
		Indices &	k_indices,
		std::vector< float > &	k_sqr_distances ) const

pure virtual

Search for the k-nearest neighbors for the given query point.

Parameters

[in]	point	the given query point
[in]	k	the number of neighbors to search for
[out]	k_indices	the resultant indices of the neighboring points (must be resized to k a priori!)
[out]	k_sqr_distances	the resultant squared distances to the neighboring points (must be resized to k a priori!)

Returns: number of neighbors found

Implemented in pcl::search::BruteForce< PointT >, pcl::search::FlannSearch< PointT, FlannDistance >, pcl::search::KdTree< PointT, Tree >, pcl::search::KdTree< pcl::PointXYZRGB >, pcl::search::KdTree< SceneT >, pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, and pcl::search::OrganizedNeighbor< PointT >.

Referenced by pcl::getPointCloudDifference(), and pcl::search::Search< PointInT >::nearestKSearchT().

◆ nearestKSearch() [4/4]

template<typename PointT>

int pcl::search::Search< PointT >::nearestKSearch	(	index_t	index,
		int	k,
		Indices &	k_indices,
		std::vector< float > &	k_sqr_distances ) const

virtual

Search for k-nearest neighbors for the given query point (zero-copy).

Attention: This method does not do any bounds checking for the input index (i.e., index >= cloud.size () || index < 0), and assumes valid (i.e., finite) data.

Parameters

[in]	index	a valid index representing a valid query point in the dataset given by setInputCloud. If indices were given in setInputCloud, index will be the position in the indices vector.
[in]	k	the number of neighbors to search for
[out]	k_indices	the resultant indices of the neighboring points (must be resized to k a priori!)
[out]	k_sqr_distances	the resultant squared distances to the neighboring points (must be resized to k a priori!)

Returns: number of neighbors found

Exceptions

asserts in debug mode if the index is not between 0 and the maximum number of points

Reimplemented in pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >.

Definition at line 96 of file search.hpp.

◆ nearestKSearchT() [1/2]

template<typename PointT>

template<typename PointTDiff>

void pcl::search::Search< PointT >::nearestKSearchT	(	const pcl::PointCloud< PointTDiff > &	cloud,
		const Indices &	indices,
		int	k,
		std::vector< Indices > &	k_indices,
		std::vector< std::vector< float > > &	k_sqr_distances ) const

inline

Search for the k-nearest neighbors for the given query point.

Use this method if the query points are of a different type than the points in the data set (e.g. PointXYZRGBA instead of PointXYZ).

Parameters

[in]	cloud	the point cloud data
[in]	indices	a vector of point cloud indices to query for nearest neighbors
[in]	k	the number of neighbors to search for
[out]	k_indices	the resultant indices of the neighboring points, k_indices[i] corresponds to the neighbors of the query point i
[out]	k_sqr_distances	the resultant squared distances to the neighboring points, k_sqr_distances[i] corresponds to the neighbors of the query point i

Note: This method copies the input point cloud of type PointTDiff to a temporary cloud of type PointT and performs the batch search on the new cloud. You should prefer the single-point search if you don't use a search algorithm that accelerates batch NN search.

Definition at line 230 of file search.h.

◆ nearestKSearchT() [2/2]

template<typename PointT>

template<typename PointTDiff>

int pcl::search::Search< PointT >::nearestKSearchT	(	const PointTDiff &	point,
		int	k,
		Indices &	k_indices,
		std::vector< float > &	k_sqr_distances ) const

inline

Search for k-nearest neighbors for the given query point.

This method accepts a different template parameter for the point type.

Parameters

[in]	point	the given query point
[in]	k	the number of neighbors to search for
[out]	k_indices	the resultant indices of the neighboring points (must be resized to k a priori!)
[out]	k_sqr_distances	the resultant squared distances to the neighboring points (must be resized to k a priori!)

Returns: number of neighbors found

Definition at line 158 of file search.h.

◆ radiusSearch() [1/4]

template<typename PointT>

void pcl::search::Search< PointT >::radiusSearch	(	const PointCloud &	cloud,
		const Indices &	indices,
		double	radius,
		std::vector< Indices > &	k_indices,
		std::vector< std::vector< float > > &	k_sqr_distances,
		unsigned int	max_nn = 0 ) const

virtual

Search for all the nearest neighbors of the query point in a given radius.

Parameters

[in]	cloud	the point cloud data
[in]	indices	the indices in cloud. If indices is empty, neighbors will be searched for all points.
[in]	radius	the radius of the sphere bounding all of p_q's neighbors
[out]	k_indices	the resultant indices of the neighboring points, k_indices[i] corresponds to the neighbors of the query point i
[out]	k_sqr_distances	the resultant squared distances to the neighboring points, k_sqr_distances[i] corresponds to the neighbors of the query point i
[in]	max_nn	if given, bounds the maximum returned neighbors to this value. If max_nn is set to 0 or to a number higher than the number of points in the input cloud, all neighbors in radius will be returned.

Reimplemented in pcl::search::FlannSearch< PointT, FlannDistance >.

Definition at line 163 of file search.hpp.

References radiusSearch(), and pcl::PointCloud< PointT >::size().

◆ radiusSearch() [2/4]

template<typename PointT>

int pcl::search::Search< PointT >::radiusSearch	(	const PointCloud &	cloud,
		index_t	index,
		double	radius,
		Indices &	k_indices,
		std::vector< float > &	k_sqr_distances,
		unsigned int	max_nn = 0 ) const

virtual

Search for all the nearest neighbors of the query point in a given radius.

Attention: This method does not do any bounds checking for the input index (i.e., index >= cloud.size () || index < 0), and assumes valid (i.e., finite) data.

Parameters

[in]	cloud	the point cloud data
[in]	index	a valid index in cloud representing a valid (i.e., finite) query point
[in]	radius	the radius of the sphere bounding all of p_q's neighbors
[out]	k_indices	the resultant indices of the neighboring points
[out]	k_sqr_distances	the resultant squared distances to the neighboring points
[in]	max_nn	if given, bounds the maximum returned neighbors to this value. If max_nn is set to 0 or to a number higher than the number of points in the input cloud, all neighbors in radius will be returned.

Returns: number of neighbors found in radius

Exceptions

asserts in debug mode if the index is not between 0 and the maximum number of points

Reimplemented in pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, and pcl::search::Octree< PointInT >.

Definition at line 137 of file search.hpp.

References radiusSearch(), and pcl::PointCloud< PointT >::size().

◆ radiusSearch() [3/4]

template<typename PointT>

virtual int pcl::search::Search< PointT >::radiusSearch	(	const PointT &	point,
		double	radius,
		Indices &	k_indices,
		std::vector< float > &	k_sqr_distances,
		unsigned int	max_nn = 0 ) const

pure virtual

Search for all the nearest neighbors of the query point in a given radius.

Parameters

[in]	point	the given query point
[in]	radius	the radius of the sphere bounding all of p_q's neighbors
[out]	k_indices	the resultant indices of the neighboring points
[out]	k_sqr_distances	the resultant squared distances to the neighboring points
[in]	max_nn	if given, bounds the maximum returned neighbors to this value. If max_nn is set to 0 or to a number higher than the number of points in the input cloud, all neighbors in radius will be returned.

Returns: number of neighbors found in radius

Implemented in pcl::search::BruteForce< PointT >, pcl::search::FlannSearch< PointT, FlannDistance >, pcl::search::KdTree< PointT, Tree >, pcl::search::KdTree< pcl::PointXYZRGB >, pcl::search::KdTree< SceneT >, pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, and pcl::search::OrganizedNeighbor< PointT >.

Referenced by pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), pcl::extractEuclideanClusters(), pcl::extractEuclideanClusters(), pcl::extractLabeledEuclideanClusters(), radiusSearch(), radiusSearch(), radiusSearch(), pcl::search::Search< PointInT >::radiusSearchT(), pcl::seededHueSegmentation(), and pcl::seededHueSegmentation().

◆ radiusSearch() [4/4]

template<typename PointT>

int pcl::search::Search< PointT >::radiusSearch	(	index_t	index,
		double	radius,
		Indices &	k_indices,
		std::vector< float > &	k_sqr_distances,
		unsigned int	max_nn = 0 ) const

virtual

Search for all the nearest neighbors of the query point in a given radius (zero-copy).

Attention: This method does not do any bounds checking for the input index (i.e., index >= cloud.size () || index < 0), and assumes valid (i.e., finite) data.

Parameters

[in]	index	a valid index representing a valid query point in the dataset given by setInputCloud. If indices were given in setInputCloud, index will be the position in the indices vector.
[in]	radius	the radius of the sphere bounding all of p_q's neighbors
[out]	k_indices	the resultant indices of the neighboring points
[out]	k_sqr_distances	the resultant squared distances to the neighboring points
[in]	max_nn	if given, bounds the maximum returned neighbors to this value. If max_nn is set to 0 or to a number higher than the number of points in the input cloud, all neighbors in radius will be returned.

Returns: number of neighbors found in radius

Exceptions

asserts in debug mode if the index is not between 0 and the maximum number of points

Reimplemented in pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >.

Definition at line 148 of file search.hpp.

References indices_, input_, and radiusSearch().

◆ radiusSearchT() [1/2]

template<typename PointT>

template<typename PointTDiff>

void pcl::search::Search< PointT >::radiusSearchT	(	const pcl::PointCloud< PointTDiff > &	cloud,
		const Indices &	indices,
		double	radius,
		std::vector< Indices > &	k_indices,
		std::vector< std::vector< float > > &	k_sqr_distances,
		unsigned int	max_nn = 0 ) const

inline

Search for all the nearest neighbors of the query points in a given radius.

Parameters

[in]	cloud	the point cloud data
[in]	indices	a vector of point cloud indices to query for nearest neighbors
[in]	radius	the radius of the sphere bounding all of p_q's neighbors
[out]	k_indices	the resultant indices of the neighboring points, k_indices[i] corresponds to the neighbors of the query point i
[out]	k_sqr_distances	the resultant squared distances to the neighboring points, k_sqr_distances[i] corresponds to the neighbors of the query point i
[in]	max_nn	if given, bounds the maximum returned neighbors to this value. If max_nn is set to 0 or to a number higher than the number of points in the input cloud, all neighbors in radius will be returned.

Note: This method copies the input point cloud of type PointTDiff to a temporary cloud of type PointT and performs the batch search on the new cloud. You should prefer the single-point search if you don't use a search algorithm that accelerates batch NN search.

Definition at line 369 of file search.h.

◆ radiusSearchT() [2/2]

template<typename PointT>

template<typename PointTDiff>

int pcl::search::Search< PointT >::radiusSearchT	(	const PointTDiff &	point,
		double	radius,
		Indices &	k_indices,
		std::vector< float > &	k_sqr_distances,
		unsigned int	max_nn = 0 ) const

inline

Search for all the nearest neighbors of the query point in a given radius.

Parameters

[in]	point	the given query point
[in]	radius	the radius of the sphere bounding all of p_q's neighbors
[out]	k_indices	the resultant indices of the neighboring points
[out]	k_sqr_distances	the resultant squared distances to the neighboring points
[in]	max_nn	if given, bounds the maximum returned neighbors to this value. If max_nn is set to 0 or to a number higher than the number of points in the input cloud, all neighbors in radius will be returned.

Returns: number of neighbors found in radius

Definition at line 286 of file search.h.

◆ setInputCloud()

template<typename PointT>

bool pcl::search::Search< PointT >::setInputCloud	(	const PointCloudConstPtr &	cloud,
		const IndicesConstPtr &	indices = IndicesConstPtr () )

virtual

Pass the input dataset that the search will be performed on.

Parameters

[in]	cloud	a const pointer to the PointCloud data
[in]	indices	the point indices subset that is to be used from the cloud

Returns: True if successful, false if an error occurred, for example because the point cloud is unsuited for the search method.

Reimplemented in pcl::search::FlannSearch< PointT, FlannDistance >, pcl::search::KdTree< PointT, Tree >, pcl::search::KdTree< pcl::PointXYZRGB >, pcl::search::KdTree< PointSource >, pcl::search::KdTree< PointTarget >, pcl::search::KdTree< SceneT >, pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, and pcl::search::OrganizedNeighbor< PointT >.

Definition at line 75 of file search.hpp.

References indices_, and input_.

◆ setSortedResults()

template<typename PointT>

void pcl::search::Search< PointT >::setSortedResults ( bool sorted )

virtual

sets whether the results should be sorted (ascending in the distance) or not

Parameters

[in] sorted should be true if the results should be sorted by the distance in ascending order. Otherwise the results may be returned in any order.

Reimplemented in pcl::search::KdTree< PointT, Tree >, pcl::search::KdTree< pcl::PointXYZRGB >, pcl::search::KdTree< PointSource >, pcl::search::KdTree< PointTarget >, and pcl::search::KdTree< SceneT >.

Definition at line 61 of file search.hpp.

References sorted_results_.

◆ sortResults()

template<typename PointT>

void pcl::search::Search< PointT >::sortResults	(	Indices &	indices,
		std::vector< float > &	distances ) const

protected

Definition at line 189 of file search.hpp.

Referenced by pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::radiusSearch(), pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::radiusSearch(), pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::radiusSearch(), and pcl::search::OrganizedNeighbor< PointT >::radiusSearch().

Member Data Documentation

◆ indices_

template<typename PointT>

IndicesConstPtr pcl::search::Search< PointT >::indices_

protected

Definition at line 403 of file search.h.

Referenced by pcl::search::FlannSearch< PointT, FlannDistance >::convertInputToFlannMatrix(), radiusSearch(), pcl::search::FlannSearch< PointT, FlannDistance >::setInputCloud(), pcl::search::KdTree< PointT, Tree >::setInputCloud(), pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::setInputCloud(), pcl::search::OrganizedNeighbor< PointT >::setInputCloud(), setInputCloud(), and pcl::search::FlannSearch< PointT, FlannDistance >::setPointRepresentation().

◆ input_

template<typename PointT>

PointCloudConstPtr pcl::search::Search< PointT >::input_

protected

Definition at line 402 of file search.h.

Referenced by pcl::search::FlannSearch< PointT, FlannDistance >::convertInputToFlannMatrix(), pcl::search::OrganizedNeighbor< PointT >::estimateProjectionMatrix(), pcl::search::OrganizedNeighbor< PointT >::getProjectedRadiusSearchBox(), pcl::search::OrganizedNeighbor< PointT >::isValid(), pcl::search::BruteForce< PointT >::nearestKSearch(), pcl::search::OrganizedNeighbor< PointT >::nearestKSearch(), pcl::search::BruteForce< PointT >::radiusSearch(), pcl::search::OrganizedNeighbor< PointT >::radiusSearch(), radiusSearch(), Search(), pcl::search::FlannSearch< PointT, FlannDistance >::setInputCloud(), pcl::search::KdTree< PointT, Tree >::setInputCloud(), pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::setInputCloud(), pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::setInputCloud(), pcl::search::OrganizedNeighbor< PointT >::setInputCloud(), setInputCloud(), pcl::search::FlannSearch< PointT, FlannDistance >::setPointRepresentation(), and pcl::search::OrganizedNeighbor< PointT >::testPoint().

◆ name_

template<typename PointT>

std::string pcl::search::Search< PointT >::name_

protected

Definition at line 405 of file search.h.

Referenced by getName(), and Search().

◆ sorted_results_

template<typename PointT>

bool pcl::search::Search< PointT >::sorted_results_

protected

Definition at line 404 of file search.h.

Referenced by getSortedResults(), pcl::search::FlannSearch< PointT, FlannDistance >::nearestKSearch(), pcl::search::FlannSearch< PointT, FlannDistance >::nearestKSearch(), pcl::search::FlannSearch< PointT, FlannDistance >::radiusSearch(), pcl::search::FlannSearch< PointT, FlannDistance >::radiusSearch(), pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::radiusSearch(), pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::radiusSearch(), pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::radiusSearch(), pcl::search::OrganizedNeighbor< PointT >::radiusSearch(), Search(), pcl::search::KdTree< PointT, Tree >::setSortedResults(), and setSortedResults().

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

pcl/search/search.h
pcl/search/impl/search.hpp

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ ConstPtr

◆ IndicesConstPtr

◆ IndicesPtr

◆ PointCloud

◆ PointCloudConstPtr

◆ PointCloudPtr

◆ Ptr

Constructor & Destructor Documentation

◆ Search()

◆ ~Search()

Member Function Documentation

◆ getIndices()

◆ getInputCloud()

◆ getName()

◆ getSortedResults()

◆ nearestKSearch() [1/4]

◆ nearestKSearch() [2/4]

◆ nearestKSearch() [3/4]

◆ nearestKSearch() [4/4]

◆ nearestKSearchT() [1/2]

◆ nearestKSearchT() [2/2]

◆ radiusSearch() [1/4]

◆ radiusSearch() [2/4]

◆ radiusSearch() [3/4]

◆ radiusSearch() [4/4]

◆ radiusSearchT() [1/2]

◆ radiusSearchT() [2/2]

◆ setInputCloud()

◆ setSortedResults()

◆ sortResults()

Member Data Documentation

◆ indices_

◆ input_

◆ name_

◆ sorted_results_