Point Cloud Library (PCL)
1.14.1-dev
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search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search functions using KdTree structure. More...
#include <pcl/search/kdtree.h>
Public Types | |
using | PointCloud = typename Search< PointT >::PointCloud |
using | PointCloudConstPtr = typename Search< PointT >::PointCloudConstPtr |
using | Ptr = shared_ptr< KdTree< PointT, Tree > > |
using | ConstPtr = shared_ptr< const KdTree< PointT, Tree > > |
using | KdTreePtr = typename Tree::Ptr |
using | KdTreeConstPtr = typename Tree::ConstPtr |
using | PointRepresentationConstPtr = typename PointRepresentation< PointT >::ConstPtr |
Public Types inherited from pcl::search::Search< PointT > | |
using | PointCloud = pcl::PointCloud< PointT > |
using | PointCloudPtr = typename PointCloud::Ptr |
using | PointCloudConstPtr = typename PointCloud::ConstPtr |
using | Ptr = shared_ptr< pcl::search::Search< PointT > > |
using | ConstPtr = shared_ptr< const pcl::search::Search< PointT > > |
using | IndicesPtr = pcl::IndicesPtr |
using | IndicesConstPtr = pcl::IndicesConstPtr |
Public Member Functions | |
KdTree (bool sorted=true) | |
Constructor for KdTree. More... | |
~KdTree () override=default | |
Destructor for KdTree. More... | |
void | setPointRepresentation (const PointRepresentationConstPtr &point_representation) |
Provide a pointer to the point representation to use to convert points into k-D vectors. More... | |
PointRepresentationConstPtr | getPointRepresentation () const |
Get a pointer to the point representation used when converting points into k-D vectors. More... | |
void | setSortedResults (bool sorted_results) override |
Sets whether the results have to be sorted or not. More... | |
void | setEpsilon (float eps) |
Set the search epsilon precision (error bound) for nearest neighbors searches. More... | |
float | getEpsilon () const |
Get the search epsilon precision (error bound) for nearest neighbors searches. More... | |
bool | setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices=IndicesConstPtr()) override |
Provide a pointer to the input dataset. More... | |
int | nearestKSearch (const PointT &point, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const override |
Search for the k-nearest neighbors for the given query point. More... | |
int | radiusSearch (const PointT &point, double radius, Indices &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const override |
Search for all the nearest neighbors of the query point in a given radius. More... | |
Public Member Functions inherited from pcl::search::Search< PointT > | |
Search (const std::string &name="", bool sorted=false) | |
Constructor. More... | |
virtual | ~Search ()=default |
Destructor. More... | |
virtual const std::string & | getName () const |
Returns the search method name. More... | |
virtual bool | getSortedResults () |
Gets whether the results should be sorted (ascending in the distance) or not Otherwise the results may be returned in any order. More... | |
virtual PointCloudConstPtr | getInputCloud () const |
Get a pointer to the input point cloud dataset. More... | |
virtual IndicesConstPtr | getIndices () const |
Get a pointer to the vector of indices used. More... | |
template<typename PointTDiff > | |
int | nearestKSearchT (const PointTDiff &point, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const |
Search for k-nearest neighbors for the given query point. More... | |
virtual int | nearestKSearch (const PointCloud &cloud, index_t index, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const |
Search for k-nearest neighbors for the given query point. More... | |
virtual int | nearestKSearch (index_t index, int k, Indices &k_indices, std::vector< float > &k_sqr_distances) const |
Search for k-nearest neighbors for the given query point (zero-copy). More... | |
virtual void | nearestKSearch (const PointCloud &cloud, const Indices &indices, int k, std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances) const |
Search for the k-nearest neighbors for the given query point. More... | |
template<typename PointTDiff > | |
void | nearestKSearchT (const pcl::PointCloud< PointTDiff > &cloud, const Indices &indices, int k, std::vector< Indices > &k_indices, std::vector< std::vector< float > > &k_sqr_distances) const |
Search for the k-nearest neighbors for the given query point. More... | |
template<typename PointTDiff > | |
int | radiusSearchT (const PointTDiff &point, double radius, Indices &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. More... | |
virtual int | radiusSearch (const PointCloud &cloud, index_t index, double radius, Indices &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. More... | |
virtual int | radiusSearch (index_t index, double radius, Indices &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). More... | |
virtual void | radiusSearch (const PointCloud &cloud, const Indices &indices, double radius, std::vector< Indices > &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. More... | |
template<typename PointTDiff > | |
void | radiusSearchT (const pcl::PointCloud< PointTDiff > &cloud, const Indices &indices, double radius, std::vector< Indices > &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. More... | |
Protected Attributes | |
KdTreePtr | tree_ |
A pointer to the internal KdTree object. More... | |
Protected Attributes inherited from pcl::search::Search< PointT > | |
PointCloudConstPtr | input_ |
IndicesConstPtr | indices_ |
bool | sorted_results_ |
std::string | name_ |
Additional Inherited Members | |
Protected Member Functions inherited from pcl::search::Search< PointT > | |
void | sortResults (Indices &indices, std::vector< float > &distances) const |
search::KdTree is a wrapper class which inherits the pcl::KdTree class for performing search functions using KdTree structure.
KdTree 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.
using pcl::search::KdTree< PointT, Tree >::ConstPtr = shared_ptr<const KdTree<PointT, Tree> > |
using pcl::search::KdTree< PointT, Tree >::KdTreeConstPtr = typename Tree::ConstPtr |
using pcl::search::KdTree< PointT, Tree >::KdTreePtr = typename Tree::Ptr |
using pcl::search::KdTree< PointT, Tree >::PointCloud = typename Search<PointT>::PointCloud |
using pcl::search::KdTree< PointT, Tree >::PointCloudConstPtr = typename Search<PointT>::PointCloudConstPtr |
using pcl::search::KdTree< PointT, Tree >::PointRepresentationConstPtr = typename PointRepresentation<PointT>::ConstPtr |
using pcl::search::KdTree< PointT, Tree >::Ptr = shared_ptr<KdTree<PointT, Tree> > |
pcl::search::KdTree< PointT, Tree >::KdTree | ( | bool | sorted = true | ) |
Constructor for KdTree.
[in] | sorted | set to true if the nearest neighbor search results need to be sorted in ascending order based on their distance to the query point |
Definition at line 45 of file kdtree.hpp.
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overridedefault |
Destructor for KdTree.
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inline |
Get the search epsilon precision (error bound) for nearest neighbors searches.
Definition at line 122 of file kdtree.h.
References pcl::search::KdTree< PointT, Tree >::tree_.
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inline |
Get a pointer to the point representation used when converting points into k-D vectors.
Definition at line 103 of file kdtree.h.
References pcl::search::KdTree< PointT, Tree >::tree_.
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overridevirtual |
Search for the k-nearest neighbors for the given query point.
[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!) |
Implements pcl::search::Search< PointT >.
Definition at line 88 of file kdtree.hpp.
Referenced by pcl::GeneralizedIterativeClosestPoint< PointSource, PointTarget, Scalar >::computeCovariances(), pcl::registration::FPCSInitialAlignment< PointSource, PointTarget, pcl::Normal, float >::FPCSInitialAlignment(), and pcl::getMeanPointDensity().
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overridevirtual |
Search for all the nearest neighbors of the query point in a given radius.
[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. |
Implements pcl::search::Search< PointT >.
Definition at line 97 of file kdtree.hpp.
Referenced by pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::refineCorners().
void pcl::search::KdTree< PointT, Tree >::setEpsilon | ( | float | eps | ) |
Set the search epsilon precision (error bound) for nearest neighbors searches.
[in] | eps | precision (error bound) for nearest neighbors searches |
Definition at line 69 of file kdtree.hpp.
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overridevirtual |
Provide a pointer to the input dataset.
[in] | cloud | the const boost shared pointer to a PointCloud message |
[in] | indices | the point indices subset that is to be used from cloud |
Reimplemented from pcl::search::Search< PointT >.
Definition at line 76 of file kdtree.hpp.
Referenced by pcl::people::GroundBasedPeopleDetectionApp< PointT >::compute(), pcl::getMeanPointDensity(), pcl::HarrisKeypoint6D< PointInT, PointOutT, NormalT >::refineCorners(), and pcl::HypothesisVerification< ModelT, SceneT >::setSceneCloud().
void pcl::search::KdTree< PointT, Tree >::setPointRepresentation | ( | const PointRepresentationConstPtr & | point_representation | ) |
Provide a pointer to the point representation to use to convert points into k-D vectors.
[in] | point_representation | the const boost shared pointer to a PointRepresentation |
Definition at line 53 of file kdtree.hpp.
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overridevirtual |
Sets whether the results have to be sorted or not.
[in] | sorted_results | set to true if the radius search results should be sorted |
Reimplemented from pcl::search::Search< PointT >.
Definition at line 61 of file kdtree.hpp.
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protected |
A pointer to the internal KdTree object.
Definition at line 165 of file kdtree.h.
Referenced by pcl::search::KdTree< PointT, Tree >::getEpsilon(), and pcl::search::KdTree< PointT, Tree >::getPointRepresentation().