Generic search class. All search wrappers must inherit from this. More...

#include <search.h>

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

Classes
struct	Compare
Public Types
typedef boost::shared_ptr < const pcl::search::Search < PointT > >	ConstPtr
typedef boost::shared_ptr < const std::vector< int > >	IndicesConstPtr
typedef boost::shared_ptr < std::vector< int > >	IndicesPtr
typedef pcl::PointCloud< PointT >	PointCloud
typedef PointCloud::ConstPtr	PointCloudConstPtr
typedef PointCloud::Ptr	PointCloudPtr
typedef boost::shared_ptr < pcl::search::Search< PointT > >	Ptr
Public Member Functions
virtual IndicesConstPtr	getIndices () const
	Get a pointer to the vector of indices used.
virtual PointCloudConstPtr	getInputCloud () const
	Get a pointer to the input point cloud dataset.
virtual const std::string &	getName () const
	Returns the search method name.
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 int	nearestKSearch (const PointT &point, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances) const =0
	Search for the k-nearest neighbors for the given query point.
virtual int	nearestKSearch (const PointCloud &cloud, int index, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances) const
	Search for k-nearest neighbors for the given query point.
virtual int	nearestKSearch (int index, int k, std::vector< int > &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 std::vector< int > &indices, int k, std::vector< std::vector< int > > &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 >
int	nearestKSearchT (const PointTDiff &point, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances) const
	Search for k-nearest neighbors for the given query point. This method accepts a different template parameter for the point type.
template<typename PointTDiff >
void	nearestKSearchT (const pcl::PointCloud< PointTDiff > &cloud, const std::vector< int > &indices, int k, std::vector< std::vector< int > > &k_indices, std::vector< std::vector< float > > &k_sqr_distances) const
	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).
virtual int	radiusSearch (const PointT &point, double radius, std::vector< int > &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.
virtual int	radiusSearch (const PointCloud &cloud, int index, double radius, std::vector< int > &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 (int index, double radius, std::vector< int > &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 std::vector< int > &indices, double radius, std::vector< std::vector< int > > &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 >
int	radiusSearchT (const PointTDiff &point, double radius, std::vector< int > &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.
template<typename PointTDiff >
void	radiusSearchT (const pcl::PointCloud< PointTDiff > &cloud, const std::vector< int > &indices, double radius, std::vector< std::vector< int > > &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.
	Search (const std::string &name="", bool sorted=false)
virtual void	setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices=IndicesConstPtr())
	Pass the input dataset that the search will be performed on.
virtual void	setSortedResults (bool sorted)
	sets whether the results should be sorted (ascending in the distance) or not
virtual	~Search ()
Protected Member Functions
void	sortResults (std::vector< int > &indices, std::vector< float > &distances) const
Protected Attributes
IndicesConstPtr	indices_
PointCloudConstPtr	input_
std::string	name_
bool	sorted_results_

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 73 of file search.h.

Member Typedef Documentation

template<typename PointT>

typedef boost::shared_ptr<const pcl::search::Search<PointT> > pcl::search::Search< PointT >::ConstPtr

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

Definition at line 81 of file search.h.

template<typename PointT>

typedef boost::shared_ptr<const std::vector<int> > pcl::search::Search< PointT >::IndicesConstPtr

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

Definition at line 84 of file search.h.

template<typename PointT>

typedef boost::shared_ptr<std::vector<int> > pcl::search::Search< PointT >::IndicesPtr

Reimplemented in pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::FlannSearch< PointT, FlannDistance >, pcl::search::KdTree< PointT >, pcl::search::KdTree< SceneT >, pcl::search::KdTree< PointTarget >, pcl::search::KdTree< pcl::PointXYZ >, and pcl::search::BruteForce< PointT >.

Definition at line 83 of file search.h.

template<typename PointT>

typedef pcl::PointCloud<PointT> pcl::search::Search< PointT >::PointCloud

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

Definition at line 76 of file search.h.

template<typename PointT>

typedef PointCloud::ConstPtr pcl::search::Search< PointT >::PointCloudConstPtr

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

Definition at line 78 of file search.h.

template<typename PointT>

typedef PointCloud::Ptr pcl::search::Search< PointT >::PointCloudPtr

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

Definition at line 77 of file search.h.

template<typename PointT>

typedef boost::shared_ptr<pcl::search::Search<PointT> > pcl::search::Search< PointT >::Ptr

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

Definition at line 80 of file search.h.

Constructor & Destructor Documentation

template<typename PointT >

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

Constructor.

Definition at line 45 of file search.hpp.

template<typename PointT>

virtual pcl::search::Search< PointT >::~Search ( ) [inline, virtual]

Destructor.

Definition at line 91 of file search.h.

Member Function Documentation

template<typename PointT>

virtual IndicesConstPtr pcl::search::Search< PointT >::getIndices ( ) const [inline, virtual]

Get a pointer to the vector of indices used.

Definition at line 131 of file search.h.

template<typename PointT>

virtual PointCloudConstPtr pcl::search::Search< PointT >::getInputCloud ( ) const [inline, virtual]

Get a pointer to the input point cloud dataset.

Definition at line 124 of file search.h.

template<typename PointT >

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

Returns the search method name.

Definition at line 55 of file search.hpp.

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 69 of file search.hpp.

template<typename PointT>

virtual int pcl::search::Search< PointT >::nearestKSearch	(	const PointT &	point,
		int	k,
		std::vector< int > &	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::FlannSearch< PointT, FlannDistance >, pcl::search::OrganizedNeighbor< PointT >, pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::KdTree< PointT >, pcl::search::KdTree< SceneT >, pcl::search::KdTree< PointTarget >, pcl::search::KdTree< pcl::PointXYZ >, and pcl::search::BruteForce< PointT >.

template<typename PointT>

int pcl::search::Search< PointT >::nearestKSearch	(	const PointCloud &	cloud,
		int	index,
		int	k,
		std::vector< int > &	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.points.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 >.

Definition at line 86 of file search.hpp.

template<typename PointT>

int pcl::search::Search< PointT >::nearestKSearch	(	int	index,
		int	k,
		std::vector< int > &	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.points.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.

template<typename PointT>

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

Definition at line 117 of file search.hpp.

template<typename PointT>

template<typename PointTDiff >

int pcl::search::Search< PointT >::nearestKSearchT	(	const PointTDiff &	point,
		int	k,
		std::vector< int > &	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.

template<typename PointT>

template<typename PointTDiff >

void pcl::search::Search< PointT >::nearestKSearchT	(	const pcl::PointCloud< PointTDiff > &	cloud,
		const std::vector< int > &	indices,
		int	k,
		std::vector< std::vector< int > > &	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 234 of file search.h.

template<typename PointT>

virtual int pcl::search::Search< PointT >::radiusSearch	(	const PointT &	point,
		double	radius,
		std::vector< int > &	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::FlannSearch< PointT, FlannDistance >, pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::KdTree< PointT >, pcl::search::KdTree< SceneT >, pcl::search::KdTree< PointTarget >, pcl::search::KdTree< pcl::PointXYZ >, pcl::search::OrganizedNeighbor< PointT >, and pcl::search::BruteForce< PointT >.

template<typename PointT>

int pcl::search::Search< PointT >::radiusSearch	(	const PointCloud &	cloud,
		int	index,
		double	radius,
		std::vector< int > &	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.points.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 >.

Definition at line 140 of file search.hpp.

template<typename PointT>

int pcl::search::Search< PointT >::radiusSearch	(	int	index,
		double	radius,
		std::vector< int > &	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.points.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 151 of file search.hpp.

template<typename PointT>

void pcl::search::Search< PointT >::radiusSearch	(	const PointCloud &	cloud,
		const std::vector< int > &	indices,
		double	radius,
		std::vector< std::vector< int > > &	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.

Definition at line 169 of file search.hpp.

template<typename PointT>

template<typename PointTDiff >

int pcl::search::Search< PointT >::radiusSearchT	(	const PointTDiff &	point,
		double	radius,
		std::vector< int > &	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 290 of file search.h.

template<typename PointT>

template<typename PointTDiff >

void pcl::search::Search< PointT >::radiusSearchT	(	const pcl::PointCloud< PointTDiff > &	cloud,
		const std::vector< int > &	indices,
		double	radius,
		std::vector< std::vector< int > > &	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 377 of file search.h.

template<typename PointT >

void 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

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

Definition at line 76 of file search.hpp.

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 >, pcl::search::KdTree< SceneT >, pcl::search::KdTree< PointTarget >, and pcl::search::KdTree< pcl::PointXYZ >.

Definition at line 62 of file search.hpp.

template<typename PointT >

void pcl::search::Search< PointT >::sortResults	(	std::vector< int > &	indices,
		std::vector< float > &	distances
	)		const `[protected]`

Definition at line 195 of file search.hpp.

Member Data Documentation

template<typename PointT>

IndicesConstPtr pcl::search::Search< PointT >::indices_ [protected]

Definition at line 411 of file search.h.

template<typename PointT>

PointCloudConstPtr pcl::search::Search< PointT >::input_ [protected]

Definition at line 410 of file search.h.

template<typename PointT>

std::string pcl::search::Search< PointT >::name_ [protected]

Definition at line 413 of file search.h.

template<typename PointT>

bool pcl::search::Search< PointT >::sorted_results_ [protected]

Definition at line 412 of file search.h.

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

Classes

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

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