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 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::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::KdTree< PointT >, 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::FlannSearch< PointT, FlannDistance >, pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::OrganizedNeighbor< PointT >, pcl::search::KdTree< PointT >, 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::FlannSearch< PointT, FlannDistance >, pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::KdTree< PointT >, 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 >, 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 >, 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::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::KdTree< PointT >, 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`
	)		`[inline]`

Constructor.

Definition at line 87 of file search.h.

template<typename PointT>

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

Destructor.

Definition at line 97 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 139 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 132 of file search.h.

template<typename PointT>

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

returns the search method name

Definition at line 104 of file search.h.

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::OrganizedNeighbor< PointT >, pcl::search::FlannSearch< PointT, FlannDistance >, pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::KdTree< PointT >, and pcl::search::BruteForce< PointT >.

template<typename PointT>

virtual 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 `[inline, 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 195 of file search.h.

template<typename PointT>

virtual int pcl::search::Search< PointT >::nearestKSearch	(	int	index,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances
	)		const `[inline, 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 220 of file search.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
	)		const `[inline, 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 245 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
	)		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 166 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 273 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::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::FlannSearch< PointT, FlannDistance >, pcl::search::KdTree< PointT >, pcl::search::OrganizedNeighbor< PointT >, and pcl::search::BruteForce< PointT >.

template<typename PointT>

virtual 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 `[inline, 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 359 of file search.h.

template<typename PointT>

virtual 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 `[inline, 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 387 of file search.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,
		unsigned int	max_nn = `0`
	)		const `[inline, 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 413 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,
		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 329 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 449 of file search.h.

template<typename PointT>

virtual void pcl::search::Search< PointT >::setInputCloud	(	const PointCloudConstPtr &	cloud,
		const IndicesConstPtr &	indices = `IndicesConstPtr ()`
	)		`[inline, 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 124 of file search.h.

template<typename PointT>

virtual void pcl::search::Search< PointT >::setSortedResults ( bool sorted ) [inline, 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 >.

Definition at line 114 of file search.h.

template<typename PointT >

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

Definition at line 504 of file search.h.

Member Data Documentation

template<typename PointT>

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

Definition at line 481 of file search.h.

template<typename PointT>

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

Definition at line 480 of file search.h.

template<typename PointT>

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

Definition at line 483 of file search.h.

template<typename PointT>

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

Definition at line 482 of file search.h.

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

search.h

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 >