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

Generic search class. More...

#include <pcl/search/search.h>

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

List of all members.

Public Types
typedef pcl::PointCloud< PointT >	PointCloud
typedef PointCloud::Ptr	PointCloudPtr
typedef PointCloud::ConstPtr	PointCloudConstPtr
typedef boost::shared_ptr < pcl::search::Search< PointT > >	Ptr
typedef boost::shared_ptr < const pcl::search::Search < PointT > >	ConstPtr
typedef boost::shared_ptr < std::vector< int > >	IndicesPtr
typedef boost::shared_ptr < const std::vector< int > >	IndicesConstPtr
Public Member Functions
	Search ()
	Constructor.
virtual	~Search ()
	Destructor.
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 PointCloudConstPtr	getInputCloud ()=0
	Get a pointer to the input point cloud dataset.
virtual IndicesConstPtr const	getIndices ()
	Get a pointer to the vector of indices used.
virtual int	nearestKSearch (const PointT &point, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances)=0
	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.
virtual int	nearestKSearch (const PointCloud &cloud, int index, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances)=0
	Search for the 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)=0
	Search for the 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)
	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 int	radiusSearch (const PointT &point, double radius, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances, int max_nn=-1) const =0
	Search for all the nearest neighbors of the query point in a given radius.
template<typename PointTDiff >
int	radiusSearchT (const PointTDiff &point, double radius, 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.
virtual int	radiusSearch (const PointCloud &cloud, int index, double radius, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances, int max_nn=-1)=0
	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, int max_nn=-1) const =0
	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, 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::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.

Definition at line 72 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::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::Search< PointT >::IndicesConstPtr

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

Definition at line 83 of file search.h.

template<typename PointT>

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

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

Definition at line 82 of file search.h.

template<typename PointT>

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

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

Definition at line 75 of file search.h.

template<typename PointT>

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

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

Definition at line 77 of file search.h.

template<typename PointT>

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

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

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::Search< PointT >::Search

(

)

[inline]

Constructor.

Definition at line 86 of file search.h.

template<typename PointT>

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

(

)

[inline, virtual]

Destructor.

Definition at line 92 of file search.h.

---

Member Function Documentation

template<typename PointT>

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

(

)

[inline, virtual]

Get a pointer to the vector of indices used.

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

Definition at line 115 of file search.h.

template<typename PointT>

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

(

)

[pure virtual]

Get a pointer to the input point cloud dataset.

Implemented in pcl::search::OrganizedNeighbor< PointT >, pcl::search::KdTree< PointT >, pcl::search::Octree< PointT, LeafTWrap, OctreeT >, pcl::search::AutotunedSearch< PointT >, and pcl::search::BruteForce< PointT >.

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
	)		[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::Octree< PointT, LeafTWrap, OctreeT >, pcl::search::KdTree< PointT >, pcl::search::AutotunedSearch< 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
	)		[pure 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_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::KdTree< PointT >, pcl::search::AutotunedSearch< PointT >, pcl::search::Octree< PointT, LeafTWrap, OctreeT >, and pcl::search::BruteForce< PointT >.

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
	)		[pure 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_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::KdTree< PointT >, pcl::search::Octree< PointT, LeafTWrap, OctreeT >, pcl::search::AutotunedSearch< PointT >, and pcl::search::BruteForce< PointT >.

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]

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]

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]

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>

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

Returns:

number of neighbors found in radius

Implemented in pcl::search::OrganizedNeighbor< PointT >, pcl::search::Octree< PointT, LeafTWrap, OctreeT >, pcl::search::KdTree< PointT >, pcl::search::AutotunedSearch< 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,
		int	max_nn = -1
	)		[pure 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_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

Implemented in pcl::search::OrganizedNeighbor< PointT >, pcl::search::KdTree< PointT >, pcl::search::AutotunedSearch< PointT >, pcl::search::Octree< PointT, LeafTWrap, OctreeT >, and pcl::search::BruteForce< PointT >.

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,
		int	max_nn = -1
	)		const [pure 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_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

Implemented in pcl::search::OrganizedNeighbor< PointT >, pcl::search::KdTree< PointT >, pcl::search::Octree< PointT, LeafTWrap, OctreeT >, pcl::search::AutotunedSearch< PointT >, and pcl::search::BruteForce< PointT >.

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]

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]

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]

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]

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]

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 >.

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

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