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

#include <organized.h>

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

Classes
struct	Entry
Public Types
typedef boost::shared_ptr < const pcl::search::OrganizedNeighbor < PointT > >	ConstPtr
typedef boost::shared_ptr < const std::vector< int > >	IndicesConstPtr
typedef pcl::PointCloud< PointT >	PointCloud
typedef boost::shared_ptr < const PointCloud >	PointCloudConstPtr
typedef boost::shared_ptr < PointCloud >	PointCloudPtr
typedef boost::shared_ptr < pcl::search::OrganizedNeighbor < PointT > >	Ptr
Public Member Functions
void	computeCameraMatrix (Eigen::Matrix3f &camera_matrix) const
	Compute the camera matrix.
void	estimateProjectionMatrix ()
	estimated the projection matrix from the input cloud.
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.
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.
	OrganizedNeighbor (bool sorted_results=false, float eps=1e-4f, unsigned pyramid_level=5)
	Constructor.
bool	projectPoint (const PointT &p, pcl::PointXY &q) const
	projects a point into the image
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.
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.
virtual	~OrganizedNeighbor ()
	Empty deconstructor.
Protected Member Functions
void	clipRange (int &begin, int &end, int min, int max) const
void	getProjectedRadiusSearchBox (const PointT &point, float squared_radius, unsigned &minX, unsigned &minY, unsigned &maxX, unsigned &maxY) const
	Obtain a search box in 2D from a sphere with a radius in 3D.
bool	testPoint (const PointT &query, unsigned k, std::priority_queue< Entry > &queue, unsigned index) const
	test if point given by index is among the k NN in results to the query point.
Protected Attributes
const float	eps_
	epsilon value for the MSE of the projection matrix estimation
Eigen::Matrix< float, 3, 3, Eigen::RowMajor >	KR_
	inveser of the left 3x3 projection matrix which is K * R (with K being the camera matrix and R the rotation matrix)
Eigen::Matrix< float, 3, 3, Eigen::RowMajor >	KR_KRT_
	inveser of the left 3x3 projection matrix which is K * R (with K being the camera matrix and R the rotation matrix)
std::vector< unsigned char >	mask_
	mask, indicating whether the point was in the indices list or not.
Eigen::Matrix< float, 3, 4, Eigen::RowMajor >	projection_matrix_
	the projection matrix. Either set by user or calculated by the first / each input cloud
const unsigned	pyramid_level_
	using only a subsample of points to calculate the projection matrix. pyramid_level_ = use down sampled cloud given by pyramid_level_

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 62 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 74 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 71 of file organized.h.

template<typename PointT>

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

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

Definition at line 67 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 70 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 68 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 73 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 88 of file organized.h.

template<typename PointT>

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

Empty deconstructor.

Definition at line 100 of file organized.h.

Member Function Documentation

template<typename PointT>

void pcl::search::OrganizedNeighbor< PointT >::clipRange	(	int &	begin,
		int &	end,
		int	min,
		int	max
	)		const `[inline, protected]`

Definition at line 239 of file organized.h.

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 330 of file organized.hpp.

template<typename PointT >

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

estimated the projection matrix from the input cloud.

Definition at line 337 of file organized.hpp.

template<typename PointT >

void pcl::search::OrganizedNeighbor< PointT >::getProjectedRadiusSearchBox	(	const PointT &	point,
		float	squared_radius,
		unsigned &	minX,
		unsigned &	minY,
		unsigned &	maxX,
		unsigned &	maxY
	)		const `[protected]`

Obtain a search box in 2D from a sphere with a radius in 3D.

Parameters:

[in]	point	the query point (sphere center)
[in]	squared_radius	the squared sphere radius
[out]	minX	the min X box coordinate
[out]	minY	the min Y box coordinate
[out]	maxX	the max X box coordinate
[out]	maxY	the max Y box coordinate

Definition at line 273 of file organized.hpp.

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 108 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

Todo:: still need to implements this functionality

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

Definition at line 117 of file organized.hpp.

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 382 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 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 129 of file organized.h.

template<typename PointT>

bool pcl::search::OrganizedNeighbor< PointT >::testPoint	(	const PointT &	query,
		unsigned	k,
		std::priority_queue< Entry > &	queue,
		unsigned	index
	)		const `[inline, protected]`

test if point given by index is among the k NN in results to the query point.

Parameters:

[in]	query	query point
[in]	k	number of maximum nn interested in
[in]	queue	priority queue with k NN
[in]	index	index on point to be tested

Returns:: wheter the top element changed or not.

Definition at line 216 of file organized.h.

Member Data Documentation

template<typename PointT>

const float pcl::search::OrganizedNeighbor< PointT >::eps_ [protected]

epsilon value for the MSE of the projection matrix estimation

Definition at line 268 of file organized.h.

template<typename PointT>

Eigen::Matrix<float, 3, 3, Eigen::RowMajor> pcl::search::OrganizedNeighbor< PointT >::KR_ [protected]

inveser of the left 3x3 projection matrix which is K * R (with K being the camera matrix and R the rotation matrix)

Definition at line 262 of file organized.h.

template<typename PointT>

Eigen::Matrix<float, 3, 3, Eigen::RowMajor> pcl::search::OrganizedNeighbor< PointT >::KR_KRT_ [protected]

inveser of the left 3x3 projection matrix which is K * R (with K being the camera matrix and R the rotation matrix)

Definition at line 265 of file organized.h.

template<typename PointT>

std::vector<unsigned char> pcl::search::OrganizedNeighbor< PointT >::mask_ [protected]

mask, indicating whether the point was in the indices list or not.

Definition at line 274 of file organized.h.

template<typename PointT>

Eigen::Matrix<float, 3, 4, Eigen::RowMajor> pcl::search::OrganizedNeighbor< PointT >::projection_matrix_ [protected]

the projection matrix. Either set by user or calculated by the first / each input cloud

Definition at line 259 of file organized.h.

template<typename PointT>

const unsigned pcl::search::OrganizedNeighbor< PointT >::pyramid_level_ [protected]

using only a subsample of points to calculate the projection matrix. pyramid_level_ = use down sampled cloud given by pyramid_level_

Definition at line 271 of file organized.h.

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

Classes

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

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

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation

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