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Point Cloud Library (PCL)
1.6.0
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Point Cloud Library (PCL)
1.6.0
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OrganizedNeighbor is a class for optimized nearest neigbhor search in organized point clouds. More...
#include <pcl/search/organized.h>
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 (bool sorted_results=false, float eps=1e-4f, unsigned pyramid_level=5) | |
| Constructor. More... | |
| virtual | ~OrganizedNeighbor () |
| Empty deconstructor. More... | |
| 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. More... | |
| void | computeCameraMatrix (Eigen::Matrix3f &camera_matrix) const |
| Compute the camera matrix. More... | |
| 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. More... | |
| 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. More... | |
| void | estimateProjectionMatrix () |
| estimated the projection matrix from the input cloud. More... | |
| 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. More... | |
| bool | projectPoint (const PointT &p, pcl::PointXY &q) const |
| projects a point into the image 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 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 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 > | |
| 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... | |
| 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 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 > | |
| 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... | |
| 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... | |
OrganizedNeighbor is a class for optimized nearest neigbhor search in organized point clouds.
Definition at line 61 of file organized.h.
| typedef boost::shared_ptr<const pcl::search::OrganizedNeighbor<PointT> > pcl::search::OrganizedNeighbor< PointT >::ConstPtr |
Definition at line 73 of file organized.h.
| typedef boost::shared_ptr<const std::vector<int> > pcl::search::OrganizedNeighbor< PointT >::IndicesConstPtr |
Definition at line 70 of file organized.h.
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inherited |
| typedef pcl::PointCloud<PointT> pcl::search::OrganizedNeighbor< PointT >::PointCloud |
Definition at line 66 of file organized.h.
| typedef boost::shared_ptr<const PointCloud> pcl::search::OrganizedNeighbor< PointT >::PointCloudConstPtr |
Definition at line 69 of file organized.h.
| typedef boost::shared_ptr<PointCloud> pcl::search::OrganizedNeighbor< PointT >::PointCloudPtr |
Definition at line 67 of file organized.h.
| typedef boost::shared_ptr<pcl::search::OrganizedNeighbor<PointT> > pcl::search::OrganizedNeighbor< PointT >::Ptr |
Definition at line 72 of file organized.h.
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inline |
Constructor.
| [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 87 of file organized.h.
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inlinevirtual |
Empty deconstructor.
Definition at line 99 of file organized.h.
| void pcl::search::OrganizedNeighbor< PointT >::computeCameraMatrix | ( | Eigen::Matrix3f & | camera_matrix) | const |
Compute the camera matrix.
| [out] | camera_matrix | the resultant computed camera matrix |
Definition at line 345 of file organized.hpp.
| void pcl::search::OrganizedNeighbor< PointT >::estimateProjectionMatrix | ( | ) |
estimated the projection matrix from the input cloud.
Definition at line 372 of file organized.hpp.
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inlinevirtualinherited |
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inlinevirtualinherited |
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inlinevirtualinherited |
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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.
Definition at line 107 of file organized.h.
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virtual |
Search for the k-nearest neighbors for a given query point.
| [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 |
Implements pcl::search::Search< PointT >.
Definition at line 113 of file organized.hpp.
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inlinevirtualinherited |
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 >.
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inlinevirtualinherited |
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 >.
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inlinevirtualinherited |
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 |
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inlineinherited |
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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inlineinherited |
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 |
| bool pcl::search::OrganizedNeighbor< PointT >::projectPoint | ( | const PointT & | p, |
| pcl::PointXY & | q | ||
| ) | const |
projects a point into the image
| [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) |
Definition at line 517 of file organized.hpp.
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virtual |
Search for all neighbors of query point that are within a given radius.
| [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. |
Implements pcl::search::Search< PointT >.
Definition at line 50 of file organized.hpp.
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inlinevirtualinherited |
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 >.
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inlinevirtualinherited |
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 >.
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inlinevirtualinherited |
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. |
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inlineinherited |
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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inlineinherited |
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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inlinevirtualinherited |
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 >, and pcl::search::KdTree< PointT >.
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inlinevirtual |
Provide a pointer to the input data set, if user has focal length he must set it before calling this.
| [in] | cloud | the const boost shared pointer to a PointCloud message |
| [in] | indices | the const boost shared pointer to PointIndices |
Definition at line 128 of file organized.h.
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inlinevirtualinherited |
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 >.
1.8.4