KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. The class is making use of the FLANN (Fast Library for Approximate Nearest Neighbor) project by Marius Muja and David Lowe. More...

#include <kdtree_flann.h>

Public Types
typedef boost::shared_ptr < const KdTreeFLANN < Eigen::MatrixXf > >	ConstPtr
typedef flann::Index < flann::L2_Simple< float > >	FLANNIndex
typedef boost::shared_ptr < const std::vector< int > >	IndicesConstPtr
typedef boost::shared_ptr < std::vector< int > >	IndicesPtr
typedef pcl::PointCloud < Eigen::MatrixXf >	PointCloud
typedef PointCloud::ConstPtr	PointCloudConstPtr
typedef pcl::PointRepresentation < Eigen::MatrixXf >	PointRepresentation
typedef boost::shared_ptr < const PointRepresentation >	PointRepresentationConstPtr
typedef boost::shared_ptr < KdTreeFLANN< Eigen::MatrixXf > >	Ptr
Public Member Functions
float	getEpsilon () const
	Get the search epsilon precision (error bound) for nearest neighbors searches.
IndicesConstPtr	getIndices () const
	Get a pointer to the vector of indices used.
PointCloudConstPtr	getInputCloud () const
	Get a pointer to the input point cloud dataset.
	KdTreeFLANN (bool sorted=true)
	Default Constructor for KdTreeFLANN.
	KdTreeFLANN (const KdTreeFLANN< Eigen::MatrixXf > &k)
	Copy constructor.
Ptr	makeShared ()
template<typename T >
int	nearestKSearch (const T &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.
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.
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).
KdTreeFLANN &	operator= (const KdTreeFLANN< Eigen::MatrixXf > &k)
	Copy operator.
template<typename T >
int	radiusSearch (const T &point, double radius, std::vector< int > &k_indices, std::vector< float > &k_sqr_dists, unsigned int max_nn=0) 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_sqr_distances, unsigned int max_nn=0) const
	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_sqr_distances, unsigned int max_nn=0) const
	Search for all the nearest neighbors of the query point in a given radius (zero-copy).
void	setEpsilon (float eps)
	Set the search epsilon precision (error bound) for nearest neighbors searches.
void	setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices=IndicesConstPtr())
	Provide a pointer to the input dataset.
virtual	~KdTreeFLANN ()
	Destructor for KdTreeFLANN. Deletes all allocated data arrays and destroys the kd-tree structures.
Protected Attributes
float	epsilon_
	Epsilon precision (error bound) for nearest neighbors searches.
IndicesConstPtr	indices_
	A pointer to the vector of point indices to use.
PointCloudConstPtr	input_
	The input point cloud dataset containing the points we need to use.
bool	sorted_
	Return the radius search neighbours sorted.
Private Member Functions
void	cleanup ()
	Internal cleanup method.
void	convertCloudToArray (const PointCloud &cloud)
	Converts a PointCloud to the internal FLANN point array representation. Returns the number of points.
void	convertCloudToArray (const PointCloud &cloud, const std::vector< int > &indices)
	Converts a PointCloud with a given set of indices to the internal FLANN point array representation. Returns the number of points.
std::string	getName () const
	Class getName method.
template<typename Expr >
bool	isRowValid (const Expr &pt) const
	Check if a given expression is valid (i.e., contains only finite values)
Private Attributes
float *	cloud_
	Internal pointer to data.
int	dim_
	Tree dimensionality (i.e. the number of dimensions per point).
FLANNIndex *	flann_index_
	A FLANN index object.
bool	identity_mapping_
	whether the mapping bwwteen internal and external indices is identity
std::vector< int >	index_mapping_
	mapping between internal and external indices.
flann::SearchParams	param_k_
	The KdTree search parameters for K-nearest neighbors.
flann::SearchParams	param_radius_
	The KdTree search parameters for radius search.
int	total_nr_points_
	The total size of the data (either equal to the number of points in the input cloud or to the number of indices - if passed).

Detailed Description

template<>
class pcl::KdTreeFLANN< Eigen::MatrixXf >

KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. The class is making use of the FLANN (Fast Library for Approximate Nearest Neighbor) project by Marius Muja and David Lowe.

Author:: Radu B. Rusu, Marius Muja

Definition at line 258 of file kdtree_flann.h.

Member Typedef Documentation

typedef boost::shared_ptr<const KdTreeFLANN<Eigen::MatrixXf> > pcl::KdTreeFLANN< Eigen::MatrixXf >::ConstPtr

Definition at line 274 of file kdtree_flann.h.

typedef flann::Index<flann::L2_Simple<float> > pcl::KdTreeFLANN< Eigen::MatrixXf >::FLANNIndex

Definition at line 267 of file kdtree_flann.h.

typedef boost::shared_ptr<const std::vector<int> > pcl::KdTreeFLANN< Eigen::MatrixXf >::IndicesConstPtr

Definition at line 265 of file kdtree_flann.h.

typedef boost::shared_ptr<std::vector<int> > pcl::KdTreeFLANN< Eigen::MatrixXf >::IndicesPtr

Definition at line 264 of file kdtree_flann.h.

typedef pcl::PointCloud<Eigen::MatrixXf> pcl::KdTreeFLANN< Eigen::MatrixXf >::PointCloud

Definition at line 261 of file kdtree_flann.h.

typedef PointCloud::ConstPtr pcl::KdTreeFLANN< Eigen::MatrixXf >::PointCloudConstPtr

Definition at line 262 of file kdtree_flann.h.

typedef pcl::PointRepresentation<Eigen::MatrixXf> pcl::KdTreeFLANN< Eigen::MatrixXf >::PointRepresentation

Definition at line 269 of file kdtree_flann.h.

typedef boost::shared_ptr<const PointRepresentation> pcl::KdTreeFLANN< Eigen::MatrixXf >::PointRepresentationConstPtr

Definition at line 270 of file kdtree_flann.h.

typedef boost::shared_ptr<KdTreeFLANN<Eigen::MatrixXf> > pcl::KdTreeFLANN< Eigen::MatrixXf >::Ptr

Definition at line 273 of file kdtree_flann.h.

Constructor & Destructor Documentation

pcl::KdTreeFLANN< Eigen::MatrixXf >::KdTreeFLANN ( bool sorted = true ) [inline]

Default Constructor for KdTreeFLANN.

Parameters:

[in] sorted set to true if the application that the tree will be used for requires sorted nearest neighbor indices (default). False otherwise.

By setting sorted to false, the radiusSearch operations will be faster.

Definition at line 281 of file kdtree_flann.h.

pcl::KdTreeFLANN< Eigen::MatrixXf >::KdTreeFLANN ( const KdTreeFLANN< Eigen::MatrixXf > & k ) [inline]

Copy constructor.

Parameters:

[in] tree the tree to copy into this

Definition at line 294 of file kdtree_flann.h.

virtual pcl::KdTreeFLANN< Eigen::MatrixXf >::~KdTreeFLANN ( ) [inline, virtual]

Destructor for KdTreeFLANN. Deletes all allocated data arrays and destroys the kd-tree structures.

Definition at line 342 of file kdtree_flann.h.

Member Function Documentation

void pcl::KdTreeFLANN< Eigen::MatrixXf >::cleanup ( ) [inline, private]

Internal cleanup method.

Definition at line 599 of file kdtree_flann.h.

void pcl::KdTreeFLANN< Eigen::MatrixXf >::convertCloudToArray ( const PointCloud & cloud ) [inline, private]

Converts a PointCloud to the internal FLANN point array representation. Returns the number of points.

Parameters:

cloud the PointCloud

Definition at line 634 of file kdtree_flann.h.

void pcl::KdTreeFLANN< Eigen::MatrixXf >::convertCloudToArray	(	const PointCloud &	cloud,
		const std::vector< int > &	indices
	)		`[inline, private]`

Converts a PointCloud with a given set of indices to the internal FLANN point array representation. Returns the number of points.

Parameters:

[in]	cloud	the PointCloud data
[in]	indices	the point cloud indices

Definition at line 675 of file kdtree_flann.h.

float pcl::KdTreeFLANN< Eigen::MatrixXf >::getEpsilon ( ) const [inline]

Get the search epsilon precision (error bound) for nearest neighbors searches.

Definition at line 591 of file kdtree_flann.h.

IndicesConstPtr pcl::KdTreeFLANN< Eigen::MatrixXf >::getIndices ( ) const [inline]

Get a pointer to the vector of indices used.

Definition at line 384 of file kdtree_flann.h.

PointCloudConstPtr pcl::KdTreeFLANN< Eigen::MatrixXf >::getInputCloud ( ) const [inline]

Get a pointer to the input point cloud dataset.

Definition at line 391 of file kdtree_flann.h.

std::string pcl::KdTreeFLANN< Eigen::MatrixXf >::getName ( ) const [inline, private]

Class getName method.

Definition at line 727 of file kdtree_flann.h.

template<typename Expr >

bool pcl::KdTreeFLANN< Eigen::MatrixXf >::isRowValid ( const Expr & pt ) const [inline, private]

Check if a given expression is valid (i.e., contains only finite values)

Parameters:

[in] pt the expression to evaluate

Definition at line 620 of file kdtree_flann.h.

Ptr pcl::KdTreeFLANN< Eigen::MatrixXf >::makeShared ( ) [inline]

Definition at line 337 of file kdtree_flann.h.

template<typename T >

int pcl::KdTreeFLANN< Eigen::MatrixXf >::nearestKSearch	(	const T &	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.

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 405 of file kdtree_flann.h.

int pcl::KdTreeFLANN< Eigen::MatrixXf >::nearestKSearch	(	const PointCloud &	cloud,
		int	index,
		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.

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

Definition at line 454 of file kdtree_flann.h.

int pcl::KdTreeFLANN< Eigen::MatrixXf >::nearestKSearch	(	int	index,
		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 (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

Definition at line 471 of file kdtree_flann.h.

KdTreeFLANN& pcl::KdTreeFLANN< Eigen::MatrixXf >::operator= ( const KdTreeFLANN< Eigen::MatrixXf > & k ) [inline]

Copy operator.

Parameters:

[in] tree the tree to copy into this

Definition at line 308 of file kdtree_flann.h.

template<typename T >

int pcl::KdTreeFLANN< Eigen::MatrixXf >::radiusSearch	(	const T &	point,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_dists,
		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_dists	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 497 of file kdtree_flann.h.

int pcl::KdTreeFLANN< Eigen::MatrixXf >::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]`

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. 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 554 of file kdtree_flann.h.

int pcl::KdTreeFLANN< Eigen::MatrixXf >::radiusSearch	(	int	index,
		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 (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. 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 574 of file kdtree_flann.h.

void pcl::KdTreeFLANN< Eigen::MatrixXf >::setEpsilon ( float eps ) [inline]

Set the search epsilon precision (error bound) for nearest neighbors searches.

Parameters:

[in] eps precision (error bound) for nearest neighbors searches

Definition at line 329 of file kdtree_flann.h.

void pcl::KdTreeFLANN< Eigen::MatrixXf >::setInputCloud	(	const PointCloudConstPtr &	cloud,
		const IndicesConstPtr &	indices = `IndicesConstPtr ()`
	)		`[inline]`

Provide a pointer to the input dataset.

Parameters:

[in]	cloud	the const boost shared pointer to a PointCloud message
[in]	indices	the point indices subset that is to be used from cloud - if NULL the whole cloud is used

Definition at line 352 of file kdtree_flann.h.

Member Data Documentation

float* pcl::KdTreeFLANN< Eigen::MatrixXf >::cloud_ [private]

Internal pointer to data.

Definition at line 733 of file kdtree_flann.h.

int pcl::KdTreeFLANN< Eigen::MatrixXf >::dim_ [private]

Tree dimensionality (i.e. the number of dimensions per point).

Definition at line 742 of file kdtree_flann.h.

float pcl::KdTreeFLANN< Eigen::MatrixXf >::epsilon_ [protected]

Epsilon precision (error bound) for nearest neighbors searches.

Definition at line 719 of file kdtree_flann.h.

FLANNIndex* pcl::KdTreeFLANN< Eigen::MatrixXf >::flann_index_ [private]

A FLANN index object.

Definition at line 730 of file kdtree_flann.h.

bool pcl::KdTreeFLANN< Eigen::MatrixXf >::identity_mapping_ [private]

whether the mapping bwwteen internal and external indices is identity

Definition at line 739 of file kdtree_flann.h.

std::vector<int> pcl::KdTreeFLANN< Eigen::MatrixXf >::index_mapping_ [private]

mapping between internal and external indices.

Definition at line 736 of file kdtree_flann.h.

IndicesConstPtr pcl::KdTreeFLANN< Eigen::MatrixXf >::indices_ [protected]

A pointer to the vector of point indices to use.

Definition at line 716 of file kdtree_flann.h.

PointCloudConstPtr pcl::KdTreeFLANN< Eigen::MatrixXf >::input_ [protected]

The input point cloud dataset containing the points we need to use.

Definition at line 713 of file kdtree_flann.h.

flann::SearchParams pcl::KdTreeFLANN< Eigen::MatrixXf >::param_k_ [private]

The KdTree search parameters for K-nearest neighbors.

Definition at line 745 of file kdtree_flann.h.

flann::SearchParams pcl::KdTreeFLANN< Eigen::MatrixXf >::param_radius_ [private]

The KdTree search parameters for radius search.

Definition at line 748 of file kdtree_flann.h.

bool pcl::KdTreeFLANN< Eigen::MatrixXf >::sorted_ [protected]

Return the radius search neighbours sorted.

Definition at line 722 of file kdtree_flann.h.

int pcl::KdTreeFLANN< Eigen::MatrixXf >::total_nr_points_ [private]

The total size of the data (either equal to the number of points in the input cloud or to the number of indices - if passed).

Definition at line 751 of file kdtree_flann.h.

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

kdtree_flann.h

Public Types

Public Member Functions

Protected Attributes

Private Member Functions

Private Attributes

Detailed Description

template<> class pcl::KdTreeFLANN< Eigen::MatrixXf >

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

template<>
class pcl::KdTreeFLANN< Eigen::MatrixXf >