Implementation of the brute force search algorithm. More...

#include <pcl/search/brute_force.h>

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

Collaboration diagram for pcl::search::BruteForce< PointT >:

Classes
struct	Entry
Public Types
typedef PointCloud::Ptr	PointCloudPtr
typedef boost::shared_ptr < pcl::search::Search< PointT > >	Ptr
typedef boost::shared_ptr < const pcl::search::Search < PointT > >	ConstPtr
Public Member Functions
	BruteForce ()
virtual	~BruteForce ()
	Destructor for KdTree.
void	setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices)
	Provide a pointer to the input dataset.
void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset.
PointCloudConstPtr	getInputCloud ()
	Get a pointer to the input dataset as passed by the user.
virtual IndicesConstPtr const	getIndices ()
	Get a pointer to the set of input indices used as passed by the user.
int	nearestKSearch (const PointT &point, int k, std::vector< int > &k_indices, std::vector< float > &k_distances)
	Search for the k-nearest neighbors for the given query point.
int	nearestKSearch (const PointCloud &cloud, int index, int k, std::vector< int > &k_indices, std::vector< float > &k_distances)
	Search for the k-nearest neighbors for the given query point.
int	nearestKSearch (int index, int k, std::vector< int > &k_indices, std::vector< float > &k_distances)
	Search for the k-nearest neighbors for the given query point (zero-copy).
int	radiusSearch (const PointT &point, double radius, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances, int max_nn=-1) const
	Search for all the nearest neighbors of the query point in a given radius.
int	radiusSearch (const PointCloud &cloud, int index, double radius, std::vector< int > &k_indices, std::vector< float > &k_distances, int max_nn=-1)
	Search for all the nearest neighbors of the query point in a given radius.
int	radiusSearch (int index, double radius, std::vector< int > &k_indices, std::vector< float > &k_distances, int max_nn=-1) const
	Search for all the nearest neighbors of the query point in a given radius (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)
	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)
	Search for the k-nearest neighbors for the given query point.
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)
	Search for the k-nearest neighbors for the given query point.
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, int max_nn=-1)
	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, int max_nn=-1)
	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, int max_nn=-1)
	Search for all the nearest neighbors of the query points in a given radius.

Detailed Description

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

Implementation of the brute force search algorithm.

Author:: Suat Gedikli <gedikli@willowgarage.com>

Definition at line 52 of file brute_force.h.

Member Typedef Documentation

template<typename PointT>

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

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

Definition at line 80 of file search.h.

template<typename PointT>

typedef PointCloud::Ptr pcl::search::Search< PointT >::PointCloudPtr [inherited]

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

Definition at line 76 of file search.h.

template<typename PointT>

typedef boost::shared_ptr<pcl::search::Search<PointT> > pcl::search::Search< PointT >::Ptr [inherited]

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

Definition at line 79 of file search.h.

Constructor & Destructor Documentation

template<typename PointT >

pcl::search::BruteForce< PointT >::BruteForce ( ) [inline]

Definition at line 75 of file brute_force.h.

template<typename PointT >

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

Destructor for KdTree.

Definition at line 81 of file brute_force.h.

Member Function Documentation

template<typename PointT >

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

Get a pointer to the set of input indices used as passed by the user.

Reimplemented from pcl::search::Search< PointT >.

Definition at line 115 of file brute_force.h.

template<typename PointT >

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

Get a pointer to the input dataset as passed by the user.

Implements pcl::search::Search< PointT >.

Definition at line 108 of file brute_force.h.

template<typename PointT >

int pcl::search::BruteForce< PointT >::nearestKSearch	(	const PointT &	point,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances
	)		`[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_distances	the resultant squared distances to the neighboring points (must be resized to k a priori!)

Returns:: number of neighbors found

Implements pcl::search::Search< PointT >.

Definition at line 57 of file brute_force.hpp.

template<typename PointT >

int pcl::search::BruteForce< PointT >::nearestKSearch	(	const PointCloud &	cloud,
		int	index,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances
	)		`[inline, virtual]`

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

Parameters:

[in]	cloud	the point cloud data
[in]	index	the index in cloud representing the 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_distances	the resultant squared distances to the neighboring points (must be resized to k a priori!)

Returns:: number of neighbors found

Implements pcl::search::Search< PointT >.

Definition at line 142 of file brute_force.h.

template<typename PointT >

int pcl::search::BruteForce< PointT >::nearestKSearch	(	int	index,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances
	)		`[inline, virtual]`

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

Parameters:

[in]	index	the index representing the 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_distances	the resultant squared distances to the neighboring points (must be resized to k a priori!)

Returns:: number of neighbors found

Implements pcl::search::Search< PointT >.

Definition at line 160 of file brute_force.h.

template<typename PointT>

virtual 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
	)		`[inline, virtual, inherited]`

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 184 of file search.h.

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
	)		`[inline, inherited]`

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. PointXYZRGB instead of PointXYZ).

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 138 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
	)		`[inline, inherited]`

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. PointXYZRGB 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 212 of file search.h.

template<typename PointT >

int pcl::search::BruteForce< PointT >::radiusSearch	(	const PointT &	point,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances,
		int	max_nn = `-1`
	)		const `[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

Returns:: number of neighbors found in radius

Implements pcl::search::Search< PointT >.

Definition at line 126 of file brute_force.hpp.

template<typename PointT >

int pcl::search::BruteForce< PointT >::radiusSearch	(	const PointCloud &	cloud,
		int	index,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances,
		int	max_nn = `-1`
	)		`[inline, virtual]`

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

Parameters:

[in]	cloud	the point cloud data
[in]	index	the index in cloud representing the 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_distances	the resultant squared distances to the neighboring points
[in]	max_nn	if given, bounds the maximum returned neighbors to this value

Returns:: number of neighbors found in radius

Implements pcl::search::Search< PointT >.

Definition at line 188 of file brute_force.h.

template<typename PointT >

int pcl::search::BruteForce< PointT >::radiusSearch	(	int	index,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances,
		int	max_nn = `-1`
	)		const `[inline, virtual]`

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

Parameters:

[in]	index	the index representing the 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_distances	the resultant squared distances to the neighboring points
[in]	max_nn	if given, bounds the maximum returned neighbors to this value

Returns:: number of neighbors found in radius

Implements pcl::search::Search< PointT >.

Definition at line 204 of file brute_force.h.

template<typename PointT>

virtual 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,
		int	max_nn = `-1`
	)		`[inline, virtual, inherited]`

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

Definition at line 312 of file search.h.

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,
		int	max_nn = `-1`
	)		`[inline, inherited]`

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

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

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

Returns:: number of neighbors found in radius

Definition at line 264 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,
		int	max_nn = `-1`
	)		`[inline, inherited]`

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 per query point to this value

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 342 of file search.h.

template<typename PointT >

void pcl::search::BruteForce< PointT >::setInputCloud	(	const PointCloudConstPtr &	cloud,
		const IndicesConstPtr &	indices
	)		`[inline, virtual]`

Provide a pointer to the input dataset.

Parameters:

cloud	the const boost shared pointer to a PointCloud message
indices	the point indices subset that is to be used from cloud

Reimplemented from pcl::search::Search< PointT >.

Definition at line 90 of file brute_force.h.

template<typename PointT >

void pcl::search::BruteForce< PointT >::setInputCloud ( const PointCloudConstPtr & cloud ) [inline, virtual]

Provide a pointer to the input dataset.

Parameters:

cloud the const boost shared pointer to a PointCloud message

Implements pcl::search::Search< PointT >.

Definition at line 100 of file brute_force.h.

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

/builddir/build/BUILD/PCL-1.4.0-Source/search/include/pcl/search/brute_force.h
/builddir/build/BUILD/PCL-1.4.0-Source/search/include/pcl/search/impl/brute_force.hpp

Classes

Public Types

Public Member Functions

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

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