pcl::search::AutotunedSearch< PointT > Class Template Reference

search::AutotunedSearch is a wrapper class which inherits all the search functions written in PCL and provides an intutive interface to all the functions. More...

#include <pcl/search/auto.h>

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

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

List of all members.

Public Types
typedef pcl::PointCloud< PointT >	PointCloud
typedef boost::shared_ptr < PointCloud >	PointCloudPtr
typedef boost::shared_ptr < const PointCloud >	PointCloudConstPtr
typedef boost::shared_ptr < pcl::search::Search< PointT > >	SearchPtr
typedef boost::shared_ptr < const pcl::search::Search < PointT > >	SearchConstPtr
typedef boost::shared_ptr < std::vector< int > >	IndicesPtr
typedef boost::shared_ptr < const std::vector< int > >	IndicesConstPtr
typedef boost::shared_ptr < pcl::search::Search< PointT > >	Ptr
typedef boost::shared_ptr < const pcl::search::Search < PointT > >	ConstPtr
Public Member Functions
	AutotunedSearch (int spatial_locator)
	constructor for AutotunedSearch.
	AutotunedSearch ()
virtual	~AutotunedSearch ()
void	initSearchDS (int spatial_locator)
	Initiate the search DS to point to spatial_locator.
void	evaluateSearchMethods (const PointCloudConstPtr &cloud, const int search_type)
	Evaluate the search Methods for the given cloud.
virtual void	setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices)
	Provide a pointer to the input dataset.
virtual PointCloudConstPtr	getInputCloud ()
	Get a pointer to the input point cloud dataset.
virtual IndicesConstPtr const	getIndices ()
	Get a pointer to the vector of indices used.
virtual void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input dataset.
int	nearestKSearch (const PointT &point, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances)
	search for 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)
	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)
	search for k-nearest neighbors for the given query point (zero-copy).
int	nearestKSearch (std::vector< PointT, Eigen::aligned_allocator< PointT > > &point, std::vector< int > &k, std::vector< std::vector< int > > &k_indices, std::vector< std::vector< float > > &k_sqr_distances)
	search for k-nearest neighbors for the given query points.
virtual int	radiusSearch (const PointT &point, const 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.
virtual 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.
virtual 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	approxNearestSearch (const PointCloudConstPtr &cloud_arg, int query_index_arg, int &result_index_arg, float &sqr_distance_arg)
	search for approximate nearest neighbor at the query point.
virtual void	approxNearestSearch (const PointT &p_q_arg, int &result_index_arg, float &sqr_distance_arg)
	search for approximate nearest neighbor at the query point.
virtual void	approxNearestSearch (int query_index_arg, int &result_index_arg, float &sqr_distance_arg)
	search for approximate nearest neighbor at the query point.
int	radiusSearch (std::vector< PointT, Eigen::aligned_allocator< PointT > > &point, std::vector< double > &radiuses, std::vector< std::vector< int > > &k_indices, std::vector< std::vector< float > > &k_distances, int max_nn) const
	Approximate search for all the nearest neighbors of the query points in the given radiuses.
int	approxRadiusSearch (const PointCloudConstPtr &cloud, int index, double radius, std::vector< int > &k_indices, std::vector< float > &k_distances, int max_nn) const
	Approximate search for all the nearest neighbors of the query point in a given radius.
int	approxNearestKSearch (const PointCloudConstPtr &cloud, int index, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances)
	Approximate search for k-nearest neighbors for the given query point.
virtual void	setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices)
	Pass the input dataset that the search will be performed on.
virtual void	setInputCloud (const PointCloudConstPtr &cloud)=0
	Pass the input dataset that the search will be performed on.
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::AutotunedSearch< PointT >

search::AutotunedSearch is a wrapper class which inherits all the search functions written in PCL and provides an intutive interface to all the functions.

Definition at line 62 of file auto.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 boost::shared_ptr<const std::vector<int> > pcl::search::AutotunedSearch< PointT >::IndicesConstPtr

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

Definition at line 73 of file auto.h.

template<typename PointT >

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

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

Definition at line 72 of file auto.h.

template<typename PointT >

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

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

Definition at line 65 of file auto.h.

template<typename PointT >

typedef boost::shared_ptr<const PointCloud> pcl::search::AutotunedSearch< PointT >::PointCloudConstPtr

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

Definition at line 67 of file auto.h.

template<typename PointT >

typedef boost::shared_ptr<PointCloud> pcl::search::AutotunedSearch< PointT >::PointCloudPtr

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

Definition at line 66 of file auto.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.

template<typename PointT >

typedef boost::shared_ptr<const pcl::search::Search<PointT> > pcl::search::AutotunedSearch< PointT >::SearchConstPtr

Definition at line 70 of file auto.h.

template<typename PointT >

typedef boost::shared_ptr<pcl::search::Search<PointT> > pcl::search::AutotunedSearch< PointT >::SearchPtr

Definition at line 69 of file auto.h.

---

Constructor & Destructor Documentation

template<typename PointT >

pcl::search::AutotunedSearch< PointT >::AutotunedSearch

(

int

spatial_locator

)

[inline]

constructor for AutotunedSearch.

Definition at line 76 of file auto.h.

template<typename PointT >

pcl::search::AutotunedSearch< PointT >::AutotunedSearch

(

)

[inline]

Definition at line 82 of file auto.h.

template<typename PointT >

virtual pcl::search::AutotunedSearch< PointT >::~AutotunedSearch

(

)

[inline, virtual]

Definition at line 89 of file auto.h.

---

Member Function Documentation

template<typename PointT >

int pcl::search::AutotunedSearch< PointT >::approxNearestKSearch	(	const PointCloudConstPtr &	cloud,
		int	index,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances
	)		[inline]

Approximate search for k-nearest neighbors for the given query point.

Parameters:

cloud	the const boost shared pointer to a PointCloud message
index	the index in cloud representing the query point
k	the number of neighbors to search for
k_indices	the resultant indices of the neighboring points (must be resized to k a priori!)
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 292 of file auto.h.

template<typename PointT >

void pcl::search::AutotunedSearch< PointT >::approxNearestSearch	(	const PointCloudConstPtr &	cloud_arg,
		int	query_index_arg,
		int &	result_index_arg,
		float &	sqr_distance_arg
	)		[virtual]

search for approximate nearest neighbor at the query point.

Parameters:

cloud_arg	the const boost shared pointer to a PointCloud message
query_index_arg	the index in cloud representing the query point
result_index_arg	the resultant index of the neighbor point
sqr_distance_arg	the resultant squared distance to the neighboring point

Returns:

number of neighbors found

Definition at line 310 of file auto.hpp.

template<typename PointT >

void pcl::search::AutotunedSearch< PointT >::approxNearestSearch	(	const PointT &	p_q_arg,
		int &	result_index_arg,
		float &	sqr_distance_arg
	)		[virtual]

search for approximate nearest neighbor at the query point.

Parameters:

p_q_arg	the given query point
result_index_arg	the resultant index of the neighbor point
sqr_distance_arg	the resultant squared distance to the neighboring point

Definition at line 322 of file auto.hpp.

template<typename PointT >

void pcl::search::AutotunedSearch< PointT >::approxNearestSearch	(	int	query_index_arg,
		int &	result_index_arg,
		float &	sqr_distance_arg
	)		[virtual]

search for approximate nearest neighbor at the query point.

Parameters:

query_index_arg	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.
result_index_arg	the resultant index of the neighbor point
sqr_distance_arg	the resultant squared distance to the neighboring point

Definition at line 334 of file auto.hpp.

template<typename PointT >

int pcl::search::AutotunedSearch< PointT >::approxRadiusSearch	(	const PointCloudConstPtr &	cloud,
		int	index,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances,
		int	max_nn
	)		const [inline]

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

Parameters:

cloud	the const boost shared pointer to a PointCloud message
index	the index in cloud representing the query point
radius	the radius of the sphere bounding all of point's neighbors
k_indices	the resultant indices of the neighboring points
k_distances	the resultant squared distances to the neighboring points
max_nn	if given, bounds the maximum returned neighbors to this value

Returns:

number of neighbors found in radius

Definition at line 276 of file auto.h.

template<typename PointT >

void pcl::search::AutotunedSearch< PointT >::evaluateSearchMethods	(	const PointCloudConstPtr &	cloud,
		const int	search_type
	)

Evaluate the search Methods for the given cloud.

Parameters:

cloud	the const boost shared pointer to a PointCloud message
search_type	the search type NEAREST_K_SEARCH and NEAREST_RADIUS_SEARCH

Definition at line 67 of file auto.hpp.

template<typename PointT >

virtual IndicesConstPtr const pcl::search::AutotunedSearch< PointT >::getIndices

(

)

[inline, virtual]

Get a pointer to the vector of indices used.

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

Definition at line 120 of file auto.h.

template<typename PointT >

virtual PointCloudConstPtr pcl::search::AutotunedSearch< PointT >::getInputCloud

(

)

[inline, virtual]

Get a pointer to the input point cloud dataset.

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

Definition at line 114 of file auto.h.

template<typename PointT >

void pcl::search::AutotunedSearch< PointT >::initSearchDS

(

int

spatial_locator

)

Initiate the search DS to point to spatial_locator.

Parameters:

spatial_locator

the spatial locator KDTREE, ORGANIZED_INDEX, OCTREE or AUTO_TUNED

Definition at line 49 of file auto.hpp.

template<typename PointT >

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

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

Parameters:

point	the given query point
k	the number of neighbors to search for
k_indices	the resultant indices of the neighboring points (must be resized to k a priori!)
k_sqr_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 253 of file auto.hpp.

template<typename PointT >

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

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

Parameters:

cloud	the point cloud data
index	the index in cloud representing the query point
k	the number of neighbors to search for
k_indices	the resultant indices of the neighboring points (must be resized to k a priori!)
k_sqr_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 262 of file auto.hpp.

template<typename PointT >

int pcl::search::AutotunedSearch< PointT >::nearestKSearch	(	int	index,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances
	)		[virtual]

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

Parameters:

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
k	the number of neighbors to search for
k_indices	the resultant indices of the neighboring points (must be resized to k a priori!)
k_sqr_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 272 of file auto.hpp.

template<typename PointT >

int pcl::search::AutotunedSearch< PointT >::nearestKSearch	(	std::vector< PointT, Eigen::aligned_allocator< PointT > > &	point,
		std::vector< int > &	k,
		std::vector< std::vector< int > > &	k_indices,
		std::vector< std::vector< float > > &	k_sqr_distances
	)		[inline]

search for k-nearest neighbors for the given query points.

Parameters:

point	the given query points
k	the numbers of the query point's neighbors to search for
k_indices	the resultant indices of the neighboring points
k_sqr_distances	the resultant squared distances to the neighboring points

Returns:

number of neighbors found

Definition at line 175 of file auto.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::AutotunedSearch< PointT >::radiusSearch	(	const PointT &	point,
		const double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_distances,
		int	max_nn = -1
	)		const [virtual]

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

Parameters:

point	the given query point
radius	the radius of the sphere bounding all of p_q's neighbors
k_indices	the resultant indices of the neighboring points
k_distances	the resultant squared distances to the neighboring points
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 281 of file auto.hpp.

template<typename PointT >

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

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

Parameters:

cloud	the point cloud data
index	the index in cloud representing the query point
radius	the radius of the sphere bounding all of p_q's neighbors
k_indices	the resultant indices of the neighboring points
k_distances	the resultant squared distances to the neighboring points
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 291 of file auto.hpp.

template<typename PointT >

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

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

Parameters:

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
radius	the radius of the sphere bounding all of p_q's neighbors
k_indices	the resultant indices of the neighboring points
k_distances	the resultant squared distances to the neighboring points
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 301 of file auto.hpp.

template<typename PointT >

int pcl::search::AutotunedSearch< PointT >::radiusSearch	(	std::vector< PointT, Eigen::aligned_allocator< PointT > > &	point,
		std::vector< double > &	radiuses,
		std::vector< std::vector< int > > &	k_indices,
		std::vector< std::vector< float > > &	k_distances,
		int	max_nn
	)		const [inline]

Approximate search for all the nearest neighbors of the query points in the given radiuses.

Parameters:

point	the given query points
radiuses	the radiuses of the sphere bounding all of point's neighbors
k_indices	the resultant indices of the neighboring points
k_distances	the resultant squared distances to the neighboring points
max_nn	if given, bounds the maximum returned neighbors to this value

Returns:

number of neighbors found in radiuses

Definition at line 258 of file auto.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>

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

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::KdTree< PointT >, and pcl::search::BruteForce< PointT >.

Definition at line 101 of file search.h.

template<typename PointT>

virtual void pcl::search::Search< PointT >::setInputCloud

(

const PointCloudConstPtr &

cloud

)

[pure virtual, inherited]

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

Parameters:

[in]

cloud

a const pointer to the PointCloud data

Implemented in pcl::search::KdTree< PointT >, and pcl::search::BruteForce< PointT >.

template<typename PointT >

void pcl::search::AutotunedSearch< PointT >::setInputCloud	(	const PointCloudConstPtr &	cloud,
		const IndicesConstPtr &	indices
	)		[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 - if NULL the whole point cloud is used

Definition at line 234 of file auto.hpp.

template<typename PointT >

void pcl::search::AutotunedSearch< PointT >::setInputCloud

(

const PointCloudConstPtr &

cloud

)

[virtual]

Provide a pointer to the input dataset.

Parameters:

cloud

the const boost shared pointer to a PointCloud message

Definition at line 244 of file auto.hpp.

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

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