Point Cloud Library (PCL)
1.7.2
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Generic search class. More...
#include <pcl/search/search.h>
Public Types | |
typedef pcl::PointCloud< PointT > | PointCloud |
typedef PointCloud::Ptr | PointCloudPtr |
typedef PointCloud::ConstPtr | PointCloudConstPtr |
typedef boost::shared_ptr < pcl::search::Search< PointT > > | Ptr |
typedef boost::shared_ptr < const pcl::search::Search < PointT > > | ConstPtr |
typedef boost::shared_ptr < std::vector< int > > | IndicesPtr |
typedef boost::shared_ptr < const std::vector< int > > | IndicesConstPtr |
Public Member Functions | |
Search (const std::string &name="", bool sorted=false) | |
Constructor. More... | |
virtual | ~Search () |
Destructor. More... | |
virtual const std::string & | getName () const |
Returns the search method name. More... | |
virtual void | setSortedResults (bool sorted) |
sets whether the results should be sorted (ascending in the distance) or not 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 void | setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices=IndicesConstPtr()) |
Pass the input dataset that the search will be performed on. 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... | |
virtual int | nearestKSearch (const PointT &point, int k, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances) const =0 |
Search for the k-nearest neighbors for the given query point. More... | |
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. More... | |
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. More... | |
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). More... | |
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. More... | |
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. More... | |
virtual int | radiusSearch (const PointT &point, double radius, std::vector< int > &k_indices, std::vector< float > &k_sqr_distances, unsigned int max_nn=0) const =0 |
Search for all the nearest neighbors of the query point in a given radius. More... | |
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. More... | |
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. More... | |
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). More... | |
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. More... | |
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. More... | |
Protected Member Functions | |
void | sortResults (std::vector< int > &indices, std::vector< float > &distances) const |
Protected Attributes | |
PointCloudConstPtr | input_ |
IndicesConstPtr | indices_ |
bool | sorted_results_ |
std::string | name_ |
Generic search class.
All search wrappers must inherit from this.
Each search method must implement 2 different types of search:
The input to each search method can be given in 3 different ways:
For the latter option, it is assumed that the user specified the input via a setInputCloud () method first.
typedef boost::shared_ptr<const pcl::search::Search<PointT> > pcl::search::Search< PointT >::ConstPtr |
typedef boost::shared_ptr<const std::vector<int> > pcl::search::Search< PointT >::IndicesConstPtr |
typedef boost::shared_ptr<std::vector<int> > pcl::search::Search< PointT >::IndicesPtr |
typedef pcl::PointCloud<PointT> pcl::search::Search< PointT >::PointCloud |
typedef PointCloud::ConstPtr pcl::search::Search< PointT >::PointCloudConstPtr |
typedef PointCloud::Ptr pcl::search::Search< PointT >::PointCloudPtr |
typedef boost::shared_ptr<pcl::search::Search<PointT> > pcl::search::Search< PointT >::Ptr |
pcl::search::Search< PointT >::Search | ( | const std::string & | name = "" , |
bool | sorted = false |
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Constructor.
Definition at line 45 of file search.hpp.
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Returns the search method name.
Definition at line 55 of file search.hpp.
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Gets whether the results should be sorted (ascending in the distance) or not Otherwise the results may be returned in any order.
Definition at line 69 of file search.hpp.
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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!) |
Implemented in pcl::search::FlannSearch< PointT, FlannDistance >, pcl::search::OrganizedNeighbor< PointT >, pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::KdTree< PointT, Tree >, pcl::search::KdTree< PointT >, pcl::search::KdTree< pcl::PointXYZRGB >, pcl::search::KdTree< SceneT >, pcl::search::KdTree< PointTarget >, and pcl::search::BruteForce< PointT >.
Referenced by pcl::search::Search< PointXYZRGB >::nearestKSearchT().
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Search for k-nearest neighbors for the given query point.
[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!) |
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 86 of file search.hpp.
References pcl::PointCloud< T >::points.
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Search for k-nearest neighbors for the given query point (zero-copy).
[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!) |
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 96 of file search.hpp.
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Search for the k-nearest neighbors for the given query point.
[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 117 of file search.hpp.
References pcl::PointCloud< T >::size().
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Search for k-nearest neighbors for the given query point.
This method accepts a different template parameter for the point type.
[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!) |
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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).
[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 |
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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. |
Implemented in pcl::search::FlannSearch< PointT, FlannDistance >, pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >, pcl::search::KdTree< PointT, Tree >, pcl::search::KdTree< PointT >, pcl::search::KdTree< pcl::PointXYZRGB >, pcl::search::KdTree< SceneT >, pcl::search::KdTree< PointTarget >, pcl::search::OrganizedNeighbor< PointT >, and pcl::search::BruteForce< PointT >.
Referenced by pcl::SmoothedSurfacesKeypoint< PointT, PointNT >::detectKeypoints(), and pcl::search::Search< PointXYZRGB >::radiusSearchT().
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Search for all the nearest neighbors of the query point in a given radius.
[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. |
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 140 of file search.hpp.
References pcl::PointCloud< T >::points.
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Search for all the nearest neighbors of the query point in a given radius (zero-copy).
[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. |
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 151 of file search.hpp.
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Search for all the nearest neighbors of the query point in a given radius.
[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 169 of file search.hpp.
References pcl::PointCloud< T >::size().
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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. |
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Search for all the nearest neighbors of the query points in a given radius.
[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. |
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Pass the input dataset that the search will be performed on.
[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 >, pcl::search::KdTree< PointT, Tree >, and pcl::search::KdTree< PointT >.
Definition at line 76 of file search.hpp.
Referenced by pcl::visualization::ImageViewer::addMask(), pcl::visualization::ImageViewer::addPlanarPolygon(), and pcl::visualization::ImageViewer::addRectangle().
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sets whether the results should be sorted (ascending in the distance) or not
[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, Tree >, pcl::search::KdTree< PointT >, pcl::search::KdTree< pcl::PointXYZRGB >, pcl::search::KdTree< SceneT >, and pcl::search::KdTree< PointTarget >.
Definition at line 62 of file search.hpp.
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Definition at line 195 of file search.hpp.
Referenced by pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::radiusSearch().
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Definition at line 405 of file search.h.
Referenced by pcl::search::Octree< PointT, LeafTWrap, BranchTWrap, OctreeT >::radiusSearch().