Point Cloud Library (PCL)
1.7.0
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KdTreeFLANN is a generic type of 3D spatial locator using kD-tree structures. More...
#include <pcl/kdtree/kdtree_flann.h>
Public Types | |
typedef KdTree< PointT > ::PointCloud | PointCloud |
typedef KdTree< PointT > ::PointCloudConstPtr | PointCloudConstPtr |
typedef boost::shared_ptr < std::vector< int > > | IndicesPtr |
typedef boost::shared_ptr < const std::vector< int > > | IndicesConstPtr |
typedef ::flann::Index< Dist > | FLANNIndex |
typedef boost::shared_ptr < KdTreeFLANN< PointT > > | Ptr |
typedef boost::shared_ptr < const KdTreeFLANN< PointT > > | ConstPtr |
Public Member Functions | |
KdTreeFLANN (bool sorted=true) | |
Default Constructor for KdTreeFLANN. | |
KdTreeFLANN (const KdTreeFLANN< PointT > &k) | |
Copy constructor. | |
KdTreeFLANN< PointT > & | operator= (const KdTreeFLANN< PointT > &k) |
Copy operator. | |
void | setEpsilon (float eps) |
Set the search epsilon precision (error bound) for nearest neighbors searches. | |
void | setSortedResults (bool sorted) |
Ptr | makeShared () |
virtual | ~KdTreeFLANN () |
Destructor for KdTreeFLANN. | |
void | setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices=IndicesConstPtr()) |
Provide a pointer to the input dataset. | |
int | nearestKSearch (const PointT &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 | radiusSearch (const PointT &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. |
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.
Definition at line 66 of file kdtree_flann.h.
typedef boost::shared_ptr<const KdTreeFLANN<PointT> > pcl::KdTreeFLANN< PointT, Dist >::ConstPtr |
Reimplemented from pcl::KdTree< PointT >.
Definition at line 87 of file kdtree_flann.h.
typedef ::flann::Index<Dist> pcl::KdTreeFLANN< PointT, Dist >::FLANNIndex |
Definition at line 83 of file kdtree_flann.h.
typedef boost::shared_ptr<const std::vector<int> > pcl::KdTreeFLANN< PointT, Dist >::IndicesConstPtr |
Reimplemented from pcl::KdTree< PointT >.
Definition at line 81 of file kdtree_flann.h.
typedef boost::shared_ptr<std::vector<int> > pcl::KdTreeFLANN< PointT, Dist >::IndicesPtr |
Reimplemented from pcl::KdTree< PointT >.
Definition at line 80 of file kdtree_flann.h.
typedef KdTree<PointT>::PointCloud pcl::KdTreeFLANN< PointT, Dist >::PointCloud |
Reimplemented from pcl::KdTree< PointT >.
Definition at line 77 of file kdtree_flann.h.
typedef KdTree<PointT>::PointCloudConstPtr pcl::KdTreeFLANN< PointT, Dist >::PointCloudConstPtr |
Reimplemented from pcl::KdTree< PointT >.
Definition at line 78 of file kdtree_flann.h.
typedef boost::shared_ptr<KdTreeFLANN<PointT> > pcl::KdTreeFLANN< PointT, Dist >::Ptr |
Reimplemented from pcl::KdTree< PointT >.
Definition at line 86 of file kdtree_flann.h.
pcl::KdTreeFLANN< PointT, Dist >::KdTreeFLANN | ( | bool | sorted = true | ) |
Default Constructor for KdTreeFLANN.
[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 49 of file kdtree_flann.hpp.
pcl::KdTreeFLANN< PointT, Dist >::KdTreeFLANN | ( | const KdTreeFLANN< PointT > & | k | ) |
Copy constructor.
[in] | tree | the tree to copy into this |
Definition at line 61 of file kdtree_flann.hpp.
virtual pcl::KdTreeFLANN< PointT, Dist >::~KdTreeFLANN | ( | ) | [inline, virtual] |
Destructor for KdTreeFLANN.
Deletes all allocated data arrays and destroys the kd-tree structures.
Definition at line 133 of file kdtree_flann.h.
Ptr pcl::KdTreeFLANN< PointT, Dist >::makeShared | ( | ) | [inline] |
Definition at line 128 of file kdtree_flann.h.
int pcl::KdTreeFLANN< PointT, Dist >::nearestKSearch | ( | const PointT & | point, |
int | k, | ||
std::vector< int > & | k_indices, | ||
std::vector< float > & | k_sqr_distances | ||
) | const [virtual] |
Search for k-nearest neighbors for the given query point.
[in] | point | a given 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!) |
asserts | in debug mode if the index is not between 0 and the maximum number of points |
Implements pcl::KdTree< PointT >.
Definition at line 132 of file kdtree_flann.hpp.
Referenced by pcl::StatisticalMultiscaleInterestRegionExtraction< PointT >::generateCloudGraph(), pcl::getApproximateIndices(), pcl::VoxelGridCovariance< PointTarget >::nearestKSearch(), pcl::ConcaveHull< PointInT >::performReconstruction(), ObjectRecognition::recognizeAndAlignPoints(), and ObjectRecognition::recognizeObject().
KdTreeFLANN<PointT>& pcl::KdTreeFLANN< PointT, Dist >::operator= | ( | const KdTreeFLANN< PointT > & | k | ) | [inline] |
Copy operator.
[in] | tree | the tree to copy into this |
Definition at line 105 of file kdtree_flann.h.
Referenced by pcl::KdTreeFLANN< GlobalDescriptorT >::operator=().
int pcl::KdTreeFLANN< PointT, Dist >::radiusSearch | ( | const PointT & | point, |
double | radius, | ||
std::vector< int > & | k_indices, | ||
std::vector< float > & | k_sqr_distances, | ||
unsigned int | max_nn = 0 |
||
) | const [virtual] |
Search for all the nearest neighbors of the query point in a given radius.
[in] | point | a given 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. |
asserts | in debug mode if the index is not between 0 and the maximum number of points |
Implements pcl::KdTree< PointT >.
Definition at line 169 of file kdtree_flann.hpp.
Referenced by pcl::VoxelGridCovariance< PointTarget >::radiusSearch(), and pcl::TextureMapping< PointInT >::textureMeshwithMultipleCameras().
void pcl::KdTreeFLANN< PointT, Dist >::setEpsilon | ( | float | eps | ) | [virtual] |
Set the search epsilon precision (error bound) for nearest neighbors searches.
[in] | eps | precision (error bound) for nearest neighbors searches |
Reimplemented from pcl::KdTree< PointT >.
Definition at line 74 of file kdtree_flann.hpp.
void pcl::KdTreeFLANN< PointT, Dist >::setInputCloud | ( | const PointCloudConstPtr & | cloud, |
const IndicesConstPtr & | indices = IndicesConstPtr () |
||
) | [virtual] |
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 - if NULL the whole cloud is used |
Reimplemented from pcl::KdTree< PointT >.
Definition at line 92 of file kdtree_flann.hpp.
Referenced by pcl::VoxelGridCovariance< PointTarget >::filter(), pcl::StatisticalMultiscaleInterestRegionExtraction< PointT >::generateCloudGraph(), pcl::getApproximateIndices(), pcl::ConcaveHull< PointInT >::performReconstruction(), ObjectRecognition::populateDatabase(), and pcl::TextureMapping< PointInT >::textureMeshwithMultipleCameras().
void pcl::KdTreeFLANN< PointT, Dist >::setSortedResults | ( | bool | sorted | ) |
Definition at line 83 of file kdtree_flann.hpp.