OrganizedNeighbor is a class for optimized nearest neigbhor search in organized point clouds. More...

#include <pcl/search/organized.h>

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

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

Classes
struct	Entry
Public Types
typedef pcl::PointCloud< PointT >	PointCloud
typedef boost::shared_ptr < PointCloud >	PointCloudPtr
typedef boost::shared_ptr < const PointCloud >	PointCloudConstPtr
typedef boost::shared_ptr < const std::vector< int > >	IndicesConstPtr
typedef boost::shared_ptr < pcl::search::OrganizedNeighbor < PointT > >	Ptr
typedef boost::shared_ptr < const pcl::search::OrganizedNeighbor < PointT > >	ConstPtr
typedef boost::shared_ptr < std::vector< int > >	IndicesPtr
Public Member Functions
	OrganizedNeighbor (bool sorted_results=false, float eps=1e-4f, unsigned pyramid_level=5)
	Constructor.
virtual	~OrganizedNeighbor ()
	Empty deconstructor.
bool	isValid () const
	Test whether this search-object is valid (input is organized AND from projective device) User should use this method after setting the input cloud, since setInput just prints an error if input is not organized or a projection matrix could not be determined.
void	computeCameraMatrix (Eigen::Matrix3f &camera_matrix) const
	Compute the camera matrix.
virtual void	setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices=IndicesConstPtr())
	Provide a pointer to the input data set, if user has focal length he must set it before calling this.
int	radiusSearch (const PointT &p_q, double radius, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const
	Search for all neighbors of query point that are within a given radius.
void	estimateProjectionMatrix ()
	estimated the projection matrix from the input cloud.
int	nearestKSearch (const PointT &p_q, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances) const
	Search for the k-nearest neighbors for a given query point.
bool	projectPoint (const PointT &p, pcl::PointXY &q) const
	projects a point into the image
virtual const std::string &	getName () const
	returns the search method name
virtual void	setSortedResults (bool sorted)
	sets whether the results should be sorted (ascending in the distance) or not
virtual void	setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices=IndicesConstPtr())
	Pass the input dataset that the search will be performed on.
virtual PointCloudConstPtr	getInputCloud () const
	Get a pointer to the input point cloud dataset.
virtual IndicesConstPtr	getIndices () const
	Get a pointer to the vector of indices used.
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.
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.
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.

Detailed Description

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

OrganizedNeighbor is a class for optimized nearest neigbhor search in organized point clouds.

Author:: Radu B. Rusu, Julius Kammerl, Suat Gedikli, Koen Buys

Definition at line 61 of file organized.h.

Member Typedef Documentation

template<typename PointT>

typedef boost::shared_ptr<const pcl::search::OrganizedNeighbor<PointT> > pcl::search::OrganizedNeighbor< PointT >::ConstPtr

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

Definition at line 73 of file organized.h.

template<typename PointT>

typedef boost::shared_ptr<const std::vector<int> > pcl::search::OrganizedNeighbor< PointT >::IndicesConstPtr

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

Definition at line 70 of file organized.h.

template<typename PointT>

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

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

Definition at line 83 of file search.h.

template<typename PointT>

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

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

Definition at line 66 of file organized.h.

template<typename PointT>

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

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

Definition at line 69 of file organized.h.

template<typename PointT>

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

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

Definition at line 67 of file organized.h.

template<typename PointT>

typedef boost::shared_ptr<pcl::search::OrganizedNeighbor<PointT> > pcl::search::OrganizedNeighbor< PointT >::Ptr

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

Definition at line 72 of file organized.h.

Constructor & Destructor Documentation

template<typename PointT>

pcl::search::OrganizedNeighbor< PointT >::OrganizedNeighbor	(	bool	sorted_results = `false`,
		float	eps = `1e-4f`,
		unsigned	pyramid_level = `5`
	)		`[inline]`

Constructor.

Parameters:

[in]	sorted_results	whether the results should be return sorted in ascending order on the distances or not. This applies only for radius search, since knn always returns sorted resutls
[in]	eps	the threshold for the mean-squared-error of the estimation of the projection matrix. if the MSE is above this value, the point cloud is considered as not from a projective device, thus organized neighbor search can not be applied on that cloud.
[in]	pyramid_level	the level of the down sampled point cloud to be used for projection matrix estimation

Definition at line 87 of file organized.h.

template<typename PointT>

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

Empty deconstructor.

Definition at line 99 of file organized.h.

Member Function Documentation

template<typename PointT >

void pcl::search::OrganizedNeighbor< PointT >::computeCameraMatrix ( Eigen::Matrix3f & camera_matrix ) const

Compute the camera matrix.

Parameters:

[out] camera_matrix the resultant computed camera matrix

Definition at line 345 of file organized.hpp.

template<typename PointT >

void pcl::search::OrganizedNeighbor< PointT >::estimateProjectionMatrix ( )

estimated the projection matrix from the input cloud.

Definition at line 372 of file organized.hpp.

template<typename PointT>

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

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, inherited]

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, inherited]

returns the search method name

Definition at line 104 of file search.h.

template<typename PointT>

bool pcl::search::OrganizedNeighbor< PointT >::isValid ( ) const [inline]

Test whether this search-object is valid (input is organized AND from projective device) User should use this method after setting the input cloud, since setInput just prints an error if input is not organized or a projection matrix could not be determined.

Returns:: true if the input data is organized and from a projective device, false otherwise

Definition at line 107 of file organized.h.

template<typename PointT >

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

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

Note:: limiting the maximum search radius (with setMaxDistance) can lead to a significant improvement in search speed

Parameters:

[in]	p_q	the given query point (setInputCloud must be given a-priori!)
[in]	k	the number of neighbors to search for (used only if horizontal and vertical window not given already!)
[out]	k_indices	the resultant point indices (must be resized to k beforehand!)
[out]	k_sqr_distances

Note:: this function does not return distances

Returns:: number of neighbors found

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

Definition at line 113 of file organized.hpp.

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, inherited]`

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, inherited]`

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, 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 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, inherited]`

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, 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. 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 >

bool pcl::search::OrganizedNeighbor< PointT >::projectPoint	(	const PointT &	p,
		pcl::PointXY &	q
	)		const

projects a point into the image

Parameters:

[in]	p	point in 3D World Coordinate Frame to be projected onto the image plane
[out]	q	the 2D projected point in pixel coordinates (u,v)

Returns:: true if projection is valid, false otherwise

Definition at line 517 of file organized.hpp.

template<typename PointT >

int pcl::search::OrganizedNeighbor< PointT >::radiusSearch	(	const PointT &	p_q,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances,
		unsigned int	max_nn = `0`
	)		const `[virtual]`

Search for all neighbors of query point that are within a given radius.

Parameters:

[in]	p_q	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

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

Definition at line 50 of file organized.hpp.

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, inherited]`

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, inherited]`

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, 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. 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, inherited]`

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, 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 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, 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::FlannSearch< PointT, FlannDistance >, and pcl::search::KdTree< PointT >.

Definition at line 124 of file search.h.

template<typename PointT>

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

Provide a pointer to the input data set, if user has focal length he must set it before calling this.

Parameters:

[in]	cloud	the const boost shared pointer to a PointCloud message
[in]	indices	the const boost shared pointer to PointIndices

Definition at line 128 of file organized.h.

template<typename PointT>

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

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.

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

/usr/src/RPM/BUILD/PCL-1.6.0-Source/search/include/pcl/search/organized.h
/usr/src/RPM/BUILD/PCL-1.6.0-Source/search/include/pcl/search/impl/organized.hpp

Classes

Public Types

Public Member Functions

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

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