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
class	NearestNeighborCandidate
	NearestNeighborCandidate entry for the nearest neighbor candidate queue.
class	RadiusSearchLoopkupEntry
	RadiusSearchLoopkupEntry entry for radius search lookup vector.
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 ()
	OrganizedNeighbor constructor.
	~OrganizedNeighbor ()
	Empty deconstructor.
void	setInputCloud (const PointCloudConstPtr &cloud)
	Provide a pointer to the input data set, if user has focal length he must set it before calling this.
void	setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices)
	Provide a pointer to the input data set, if user has focal length he must set it before calling this.
PointCloudConstPtr	getInputCloud ()
	Get a pointer to the input dataset as passed by the user.
IndicesConstPtr const	getIndices ()
	Get a pointer to the Indices.
void	setPrecision (int precision)
	Set which of the two available nearest neighbor estimation methods should be used (approximate = 0 or exact = 1).
int	getPrecision ()
	Obtain which of the nearest neighbor method is being used.
void	setOneOverFocalLength (double oneOverFocalLength)
	Set the focal length, this should be done before calling set InputCloud.
double	getOneOverFocalLength ()
	Get the 1/focallength, can be the set or calculated one.
double	getMaxDistance () const
	Get the maximum allowed distance between the query point and its nearest neighbors.
void	setMaxDistance (double max_dist)
	Set the maximum allowed distance between the query point and its nearest neighbors.
void	setSearchWindow (int horizontal, int vertical)
	set the search window (horizontal, vertical) in pixels.
void	setSearchWindowAsK (int k)
	Estimate the search window (horizontal, vertical) in pixels in order to get up to k-neighbors.
int	getHorizontalSearchWindow () const
	Get the horizontal search window in pixels.
int	getVerticalSearchWindow () const
	Get the vertical search window in pixels.
int	radiusSearch (const PointCloud &cloud, int index, double radius, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances, int max_nn=std::numeric_limits< int >::max())
	Search for all the nearest neighbors of the query point in a given radius.
int	radiusSearch (const PointCloudConstPtr &cloud, int index, double radius, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances, int max_nn=std::numeric_limits< int >::max())
	Search for all neighbors of query point that are within a given radius.
int	radiusSearch (int index, const double radius, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances, int max_nn=std::numeric_limits< int >::max()) const
	Search for all neighbors of query point that are within a given radius.
int	radiusSearch (const PointT &p_q, const double radius, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances, int max_nn=std::numeric_limits< int >::max()) const
	Search for all neighbors of query point that are within a given radius.
double	estimateFocalLengthFromInputCloud (const pcl::PointCloud< PointT > &cloud)
	Estimate the focal length parameter that was used during point cloud generation.
int	exactNearestKSearch (const PointT &p_q, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances)
	Search for the k-nearest neighbors for a given query point.
int	exactNearestKSearch (int index, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances)
	Search for the k-nearest neighbors for the given query point (zero-copy).
int	exactNearestKSearch (const pcl::PointCloud< PointT > &cloud, int index, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances)
	Search for the k-nearest neighbors for a given query point.
int	nearestKSearch (const PointT &p_q, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances)
	Search for the k-nearest neighbors for a given query point.
int	nearestKSearch (int index, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances)
	Search for the k-nearest neighbors for the given query point (zero-copy).
int	nearestKSearch (const pcl::PointCloud< PointT > &cloud, int index, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances)
	Search for the k-nearest neighbors for a given query point.
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 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 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 >
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.
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 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 >
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.
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::OrganizedNeighbor< PointT >

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

The current API implements two different methods in the same corpus:

a fast, simple but approximate, window-based nearest neighbor estimation method, similar to 2D
a slower, but more accurate spherical projection method

You can switch between the two methods using setPrecision (true/false). By default the class uses the faster approximate method.

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

Definition at line 68 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 80 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 77 of file organized.h.

template<typename PointT>

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

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::OrganizedNeighbor< PointT >::PointCloud

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

Definition at line 73 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 76 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 74 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 79 of file organized.h.

Constructor & Destructor Documentation

template<typename PointT >

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

OrganizedNeighbor constructor.

Definition at line 83 of file organized.h.

template<typename PointT >

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

Empty deconstructor.

Definition at line 96 of file organized.h.

Member Function Documentation

template<typename PointT >

double pcl::search::OrganizedNeighbor< PointT >::estimateFocalLengthFromInputCloud ( const pcl::PointCloud< PointT > & cloud )

Estimate the focal length parameter that was used during point cloud generation.

Parameters:

[in] cloud the input point cloud dataset

Returns:: oneOverFocalLength

Definition at line 312 of file organized.hpp.

template<typename PointT >

int pcl::search::OrganizedNeighbor< PointT >::exactNearestKSearch	(	const PointT &	p_q,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances
	)

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

Parameters:

[in]	p_q	the given query point
[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

Definition at line 159 of file organized.hpp.

template<typename PointT >

int pcl::search::OrganizedNeighbor< PointT >::exactNearestKSearch	(	int	index,
		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 (zero-copy).

Parameters:

[in]	index	the index representing the query point in the dataset given by setInputCloud
[in]	k	the number of neighbors to search for
[out]	k_indices	the resultant point indices
[out]	k_sqr_distances	the resultant point neighbor distances

Returns:: number of neighbors found

Definition at line 131 of file organized.hpp.

template<typename PointT >

int pcl::search::OrganizedNeighbor< PointT >::exactNearestKSearch	(	const pcl::PointCloud< PointT > &	cloud,
		int	index,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances
	)		`[inline]`

Search for the k-nearest neighbors for a 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 (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

template<typename PointT >

int pcl::search::OrganizedNeighbor< PointT >::getHorizontalSearchWindow ( ) const [inline]

Get the horizontal search window in pixels.

Definition at line 213 of file organized.h.

template<typename PointT >

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

Get a pointer to the Indices.

Returns:: the boost shared pointer to the indices list

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

Definition at line 157 of file organized.h.

template<typename PointT >

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

Get a pointer to the input dataset as passed by the user.

Returns:: the const boost shared pointer to a pointcloud

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

Definition at line 151 of file organized.h.

template<typename PointT >

double pcl::search::OrganizedNeighbor< PointT >::getMaxDistance ( ) const [inline]

Get the maximum allowed distance between the query point and its nearest neighbors.

Definition at line 186 of file organized.h.

template<typename PointT >

double pcl::search::OrganizedNeighbor< PointT >::getOneOverFocalLength ( ) [inline]

Get the 1/focallength, can be the set or calculated one.

Definition at line 182 of file organized.h.

template<typename PointT >

int pcl::search::OrganizedNeighbor< PointT >::getPrecision ( ) [inline]

Obtain which of the nearest neighbor method is being used.

Definition at line 168 of file organized.h.

template<typename PointT >

int pcl::search::OrganizedNeighbor< PointT >::getVerticalSearchWindow ( ) const [inline]

Get the vertical search window in pixels.

Definition at line 217 of file organized.h.

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, inherited]`

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 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, 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 184 of file search.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
	)		`[inline, 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 346 of file organized.h.

template<typename PointT >

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

Search for the k-nearest neighbors for the given query point (zero-copy).

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

Parameters:

[in]	index	the index representing the query point in the dataset (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 170 of file organized.hpp.

template<typename PointT >

int pcl::search::OrganizedNeighbor< PointT >::nearestKSearch	(	const pcl::PointCloud< PointT > &	cloud,
		int	index,
		int	k,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances
	)

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]	cloud	the point cloud data
[in]	index	the index in cloud representing the query point
[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

Definition at line 142 of file organized.hpp.

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, 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. 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, 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. 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 >

int pcl::search::OrganizedNeighbor< PointT >::radiusSearch	(	const PointCloud &	cloud,
		int	index,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances,
		int	max_nn = `std::numeric_limits<int>::max ()`
	)		`[inline, 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

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

Definition at line 229 of file organized.h.

template<typename PointT >

int pcl::search::OrganizedNeighbor< PointT >::radiusSearch	(	const PointCloudConstPtr &	cloud,
		int	index,
		double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances,
		int	max_nn = `std::numeric_limits<int>::max ()`
	)

Search for all neighbors of query point that are within 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

Definition at line 47 of file organized.hpp.

template<typename PointT >

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

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

Parameters:

[in]	index	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	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

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

Definition at line 60 of file organized.hpp.

template<typename PointT >

int pcl::search::OrganizedNeighbor< PointT >::radiusSearch	(	const PointT &	p_q,
		const double	radius,
		std::vector< int > &	k_indices,
		std::vector< float > &	k_sqr_distances,
		int	max_nn = `std::numeric_limits<int>::max ()`
	)		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

Returns:: number of neighbors found in radius

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

Definition at line 72 of file organized.hpp.

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, 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

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, inherited]`

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, 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 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, 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::KdTree< PointT >, and pcl::search::BruteForce< PointT >.

Definition at line 101 of file search.h.

template<typename PointT >

void pcl::search::OrganizedNeighbor< PointT >::setInputCloud ( const PointCloudConstPtr & cloud ) [inline]

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

Definition at line 102 of file organized.h.

template<typename PointT>

virtual void pcl::search::Search< PointT >::setInputCloud ( const PointCloudConstPtr & cloud ) [pure virtual, inherited]

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 >.

template<typename PointT >

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

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 127 of file organized.h.

template<typename PointT >

void pcl::search::OrganizedNeighbor< PointT >::setMaxDistance ( double max_dist ) [inline]

Set the maximum allowed distance between the query point and its nearest neighbors.

Parameters:

[in] max_dist the maximul allowed distance between the query point and its nearest neighbors

Definition at line 192 of file organized.h.

template<typename PointT >

void pcl::search::OrganizedNeighbor< PointT >::setOneOverFocalLength ( double oneOverFocalLength ) [inline]

Set the focal length, this should be done before calling set InputCloud.

Parameters:

[in] oneOverFocalLength the focal length

Definition at line 174 of file organized.h.

template<typename PointT >

void pcl::search::OrganizedNeighbor< PointT >::setPrecision ( int precision ) [inline]

Set which of the two available nearest neighbor estimation methods should be used (approximate = 0 or exact = 1).

Parameters:

[in] precision set to 0 for the faster, approximate nearest neighbor search method, 1 otherwise

Definition at line 164 of file organized.h.

template<typename PointT >

void pcl::search::OrganizedNeighbor< PointT >::setSearchWindow	(	int	horizontal,
		int	vertical
	)		`[inline]`

set the search window (horizontal, vertical) in pixels.

Parameters:

[in]	horizontal	the horizontal window in pixel
[in]	vertical	the vertical window in pixel

Definition at line 199 of file organized.h.

template<typename PointT >

void pcl::search::OrganizedNeighbor< PointT >::setSearchWindowAsK ( int k )

Estimate the search window (horizontal, vertical) in pixels in order to get up to k-neighbors.

Parameters:

[in] k the number of neighbors requested

Definition at line 389 of file organized.hpp.

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

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