PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals. More...
#include <pcl/features/pfh.h>
Public Types |
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| using | Ptr = shared_ptr< PFHEstimation< PointInT, PointNT, PointOutT > > |
| using | ConstPtr = shared_ptr< const PFHEstimation< PointInT, PointNT, PointOutT > > |
| using | PointCloudOut = typename Feature< PointInT, PointOutT >::PointCloudOut |
| using | PointCloudIn = typename Feature< PointInT, PointOutT >::PointCloudIn |
 Public Types inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 > |
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| using | PointCloudN = pcl::PointCloud< PointNT > |
| using | PointCloudNPtr = typename PointCloudN::Ptr |
| using | PointCloudNConstPtr = typename PointCloudN::ConstPtr |
| using | Ptr = shared_ptr< FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 > > |
| using | ConstPtr = shared_ptr< const FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 > > |
| Public Types inherited from pcl::Feature< PointInT, pcl::PFHSignature125 > |
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| using | BaseClass = PCLBase< PointInT > |
| using | Ptr = shared_ptr< Feature< PointInT, pcl::PFHSignature125 > > |
| using | ConstPtr = shared_ptr< const Feature< PointInT, pcl::PFHSignature125 > > |
| using | KdTree = pcl::search::Search< PointInT > |
| using | KdTreePtr = typename KdTree::Ptr |
| using | PointCloudIn = pcl::PointCloud< PointInT > |
| using | PointCloudInPtr = typename PointCloudIn::Ptr |
| using | PointCloudInConstPtr = typename PointCloudIn::ConstPtr |
| using | PointCloudOut = pcl::PointCloud< pcl::PFHSignature125 > |
| using | SearchMethod = std::function< int(std::size_t, double, pcl::Indices &, std::vector< float > &)> |
| using | SearchMethodSurface = std::function< int(const PointCloudIn &cloud, std::size_t index, double, pcl::Indices &, std::vector< float > &)> |
| Public Types inherited from pcl::PCLBase< PointInT > |
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| using | PointCloud = pcl::PointCloud< PointInT > |
| using | PointCloudPtr = typename PointCloud::Ptr |
| using | PointCloudConstPtr = typename PointCloud::ConstPtr |
| using | PointIndicesPtr = PointIndices::Ptr |
| using | PointIndicesConstPtr = PointIndices::ConstPtr |
Public Member Functions |
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| PFHEstimation () | |
| Empty constructor. More... |
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| void | setMaximumCacheSize (unsigned int cache_size) |
| Set the maximum internal cache size. More... |
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| unsigned int | getMaximumCacheSize () |
| Get the maximum internal cache size. More... |
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| void | setUseInternalCache (bool use_cache) |
| Set whether to use an internal cache mechanism for removing redundant calculations or not. More... |
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| bool | getUseInternalCache () |
| Get whether the internal cache is used or not for computing the PFH features. More... |
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| bool | computePairFeatures (const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, int p_idx, int q_idx, float &f1, float &f2, float &f3, float &f4) |
| Compute the 4-tuple representation containing the three angles and one distance between two points represented by Cartesian coordinates and normals. More... |
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| void | computePointPFHSignature (const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, const pcl::Indices &indices, int nr_split, Eigen::VectorXf &pfh_histogram) |
| Estimate the PFH (Point Feature Histograms) individual signatures of the three angular (f1, f2, f3) features for a given point based on its spatial neighborhood of 3D points with normals. More... |
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| Public Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 > |
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| FeatureFromNormals () | |
| Empty constructor. More... |
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| virtual | ~FeatureFromNormals () |
| Empty destructor. More... |
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| void | setInputNormals (const PointCloudNConstPtr &normals) |
| Provide a pointer to the input dataset that contains the point normals of the XYZ dataset. More... |
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| PointCloudNConstPtr | getInputNormals () const |
| Get a pointer to the normals of the input XYZ point cloud dataset. More... |
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| Public Member Functions inherited from pcl::Feature< PointInT, pcl::PFHSignature125 > |
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| Feature () | |
| Empty constructor. More... |
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| virtual | ~Feature () |
| Empty destructor. More... |
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| void | setSearchSurface (const PointCloudInConstPtr &cloud) |
| Provide a pointer to a dataset to add additional information to estimate the features for every point in the input dataset. More... |
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| PointCloudInConstPtr | getSearchSurface () const |
| Get a pointer to the surface point cloud dataset. More... |
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| void | setSearchMethod (const KdTreePtr &tree) |
| Provide a pointer to the search object. More... |
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| KdTreePtr | getSearchMethod () const |
| Get a pointer to the search method used. More... |
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| double | getSearchParameter () const |
| Get the internal search parameter. More... |
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| void | setKSearch (int k) |
| Set the number of k nearest neighbors to use for the feature estimation. More... |
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| int | getKSearch () const |
| get the number of k nearest neighbors used for the feature estimation. More... |
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| void | setRadiusSearch (double radius) |
| Set the sphere radius that is to be used for determining the nearest neighbors used for the feature estimation. More... |
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| double | getRadiusSearch () const |
| Get the sphere radius used for determining the neighbors. More... |
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| void | compute (PointCloudOut &output) |
| Base method for feature estimation for all points given in <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () More... |
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| Public Member Functions inherited from pcl::PCLBase< PointInT > |
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| PCLBase () | |
| Empty constructor. More... |
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| PCLBase (const PCLBase &base) | |
| Copy constructor. More... |
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| virtual | ~PCLBase ()=default |
| Destructor. More... |
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| virtual void | setInputCloud (const PointCloudConstPtr &cloud) |
| Provide a pointer to the input dataset. More... |
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| const PointCloudConstPtr | getInputCloud () const |
| Get a pointer to the input point cloud dataset. More... |
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| virtual void | setIndices (const IndicesPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (const IndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (const PointIndicesConstPtr &indices) |
| Provide a pointer to the vector of indices that represents the input data. More... |
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| virtual void | setIndices (std::size_t row_start, std::size_t col_start, std::size_t nb_rows, std::size_t nb_cols) |
| Set the indices for the points laying within an interest region of the point cloud. More... |
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| IndicesPtr | getIndices () |
| Get a pointer to the vector of indices used. More... |
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| const IndicesConstPtr | getIndices () const |
| Get a pointer to the vector of indices used. More... |
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| const PointInT & | operator[] (std::size_t pos) const |
| Override PointCloud operator[] to shorten code. More... |
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Protected Member Functions |
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| void | computeFeature (PointCloudOut &output) override |
| Estimate the Point Feature Histograms (PFH) descriptors at a set of points given by <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod () More... |
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| Protected Member Functions inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 > |
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| virtual bool | initCompute () |
| This method should get called before starting the actual computation. More... |
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| Protected Member Functions inherited from pcl::Feature< PointInT, pcl::PFHSignature125 > |
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| const std::string & | getClassName () const |
| Get a string representation of the name of this class. More... |
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| virtual bool | deinitCompute () |
| This method should get called after ending the actual computation. More... |
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| int | searchForNeighbors (std::size_t index, double parameter, pcl::Indices &indices, std::vector< float > &distances) const |
| Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface. More... |
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| int | searchForNeighbors (const PointCloudIn &cloud, std::size_t index, double parameter, pcl::Indices &indices, std::vector< float > &distances) const |
| Search for k-nearest neighbors using the spatial locator from setSearchmethod, and the given surface from setSearchSurface. More... |
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| Protected Member Functions inherited from pcl::PCLBase< PointInT > |
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| bool | initCompute () |
| This method should get called before starting the actual computation. More... |
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| bool | deinitCompute () |
| This method should get called after finishing the actual computation. More... |
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Protected Attributes |
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| int | nr_subdiv_ |
| The number of subdivisions for each angular feature interval. More... |
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| Eigen::VectorXf | pfh_histogram_ |
| Placeholder for a point's PFH signature. More... |
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| Eigen::Vector4f | pfh_tuple_ |
| Placeholder for a PFH 4-tuple. More... |
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| int | f_index_ [3] |
| Placeholder for a histogram index. More... |
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| float | d_pi_ |
| Float constant = 1.0 / (2.0 * M_PI) More... |
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| std::map< std::pair< int, int >, Eigen::Vector4f, std::less<>, Eigen::aligned_allocator< std::pair< const std::pair< int, int >, Eigen::Vector4f > > > | feature_map_ |
| Internal hashmap, used to optimize efficiency of redundant computations. More... |
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| std::queue< std::pair< int, int > > | key_list_ |
| Queue of pairs saved, used to constrain memory usage. More... |
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| unsigned int | max_cache_size_ |
| Maximum size of internal cache memory. More... |
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| bool | use_cache_ |
| Set to true to use the internal cache for removing redundant computations. More... |
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| Protected Attributes inherited from pcl::FeatureFromNormals< PointInT, PointNT, pcl::PFHSignature125 > |
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| PointCloudNConstPtr | normals_ |
| A pointer to the input dataset that contains the point normals of the XYZ dataset. More... |
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| Protected Attributes inherited from pcl::Feature< PointInT, pcl::PFHSignature125 > |
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| std::string | feature_name_ |
| The feature name. More... |
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| SearchMethodSurface | search_method_surface_ |
| The search method template for points. More... |
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| PointCloudInConstPtr | surface_ |
| An input point cloud describing the surface that is to be used for nearest neighbors estimation. More... |
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| KdTreePtr | tree_ |
| A pointer to the spatial search object. More... |
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| double | search_parameter_ |
| The actual search parameter (from either search_radius_ or k_). More... |
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| double | search_radius_ |
| The nearest neighbors search radius for each point. More... |
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| int | k_ |
| The number of K nearest neighbors to use for each point. More... |
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| bool | fake_surface_ |
| If no surface is given, we use the input PointCloud as the surface. More... |
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| Protected Attributes inherited from pcl::PCLBase< PointInT > |
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| PointCloudConstPtr | input_ |
| The input point cloud dataset. More... |
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| IndicesPtr | indices_ |
| A pointer to the vector of point indices to use. More... |
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| bool | use_indices_ |
| Set to true if point indices are used. More... |
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| bool | fake_indices_ |
| If no set of indices are given, we construct a set of fake indices that mimic the input PointCloud. More... |
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Detailed Description
template<typename PointInT, typename PointNT, typename PointOutT = pcl::PFHSignature125>
class pcl::PFHEstimation< PointInT, PointNT, PointOutT >
PFHEstimation estimates the Point Feature Histogram (PFH) descriptor for a given point cloud dataset containing points and normals.
A commonly used type for PointOutT is pcl::PFHSignature125.
- Note
- If you use this code in any academic work, please cite:
- R.B. Rusu, N. Blodow, Z.C. Marton, M. Beetz. Aligning Point Cloud Views using Persistent Feature Histograms. In Proceedings of the 21st IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Nice, France, September 22-26 2008.
- R.B. Rusu, Z.C. Marton, N. Blodow, M. Beetz. Learning Informative Point Classes for the Acquisition of Object Model Maps. In Proceedings of the 10th International Conference on Control, Automation, Robotics and Vision (ICARCV), Hanoi, Vietnam, December 17-20 2008.
- Attention
-
The convention for PFH features is:
- if a query point's nearest neighbors cannot be estimated, the PFH feature will be set to NaN (not a number)
- it is impossible to estimate a PFH descriptor for a point that doesn't have finite 3D coordinates. Therefore, any point that contains NaN data on x, y, or z, will have its PFH feature property set to NaN.
- Note
- The code is stateful as we do not expect this class to be multicore parallelized. Please look at FPFHEstimationOMP for examples on parallel implementations of the FPFH (Fast Point Feature Histogram).
Member Typedef Documentation
ConstPtr
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
| using pcl::PFHEstimation< PointInT, PointNT, PointOutT >::ConstPtr = shared_ptr<const PFHEstimation<PointInT, PointNT, PointOutT> > |
PointCloudIn
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
| using pcl::PFHEstimation< PointInT, PointNT, PointOutT >::PointCloudIn = typename Feature<PointInT, PointOutT>::PointCloudIn |
PointCloudOut
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
| using pcl::PFHEstimation< PointInT, PointNT, PointOutT >::PointCloudOut = typename Feature<PointInT, PointOutT>::PointCloudOut |
Ptr
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
| using pcl::PFHEstimation< PointInT, PointNT, PointOutT >::Ptr = shared_ptr<PFHEstimation<PointInT, PointNT, PointOutT> > |
Constructor & Destructor Documentation
PFHEstimation()
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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inline |
Empty constructor.
Sets use_cache_ to false, nr_subdiv_ to 5, and the internal maximum cache size to 1GB.
Definition at line 101 of file pfh.h.
References pcl::Feature< PointInT, pcl::PFHSignature125 >::feature_name_.
Member Function Documentation
computeFeature()
template<typename PointInT , typename PointNT , typename PointOutT >
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overrideprotected |
Estimate the Point Feature Histograms (PFH) descriptors at a set of points given by <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in setSearchMethod ()
- Parameters
-
[out] output the resultant point cloud model dataset that contains the PFH feature estimates
Definition at line 167 of file pfh.hpp.
References pcl::isFinite().
computePairFeatures()
template<typename PointInT , typename PointNT , typename PointOutT >
| bool pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computePairFeatures | ( | const pcl::PointCloud< PointInT > & | cloud, |
| const pcl::PointCloud< PointNT > & | normals, | ||
| int | p_idx, | ||
| int | q_idx, | ||
| float & | f1, | ||
| float & | f2, | ||
| float & | f3, | ||
| float & | f4 | ||
| ) |
Compute the 4-tuple representation containing the three angles and one distance between two points represented by Cartesian coordinates and normals.
- Note
- For explanations about the features, please see the literature mentioned above (the order of the features might be different).
- Parameters
-
[in] cloud the dataset containing the XYZ Cartesian coordinates of the two points [in] normals the dataset containing the surface normals (assuming normalized vectors) at each point in cloud [in] p_idx the index of the first point (source) [in] q_idx the index of the second point (target) [out] f1 the first angular feature (angle between the projection of nq_idx and u) [out] f2 the second angular feature (angle between nq_idx and v) [out] f3 the third angular feature (angle between np_idx and |p_idx - q_idx|) [out] f4 the distance feature (p_idx - q_idx)
- Note
- For efficiency reasons, we assume that the point data passed to the method is finite.
Definition at line 49 of file pfh.hpp.
References pcl::computePairFeatures().
computePointPFHSignature()
template<typename PointInT , typename PointNT , typename PointOutT >
| void pcl::PFHEstimation< PointInT, PointNT, PointOutT >::computePointPFHSignature | ( | const pcl::PointCloud< PointInT > & | cloud, |
| const pcl::PointCloud< PointNT > & | normals, | ||
| const pcl::Indices & | indices, | ||
| int | nr_split, | ||
| Eigen::VectorXf & | pfh_histogram | ||
| ) |
Estimate the PFH (Point Feature Histograms) individual signatures of the three angular (f1, f2, f3) features for a given point based on its spatial neighborhood of 3D points with normals.
- Parameters
-
[in] cloud the dataset containing the XYZ Cartesian coordinates of the two points [in] normals the dataset containing the surface normals at each point in cloud [in] indices the k-neighborhood point indices in the dataset [in] nr_split the number of subdivisions for each angular feature interval [out] pfh_histogram the resultant (combinatorial) PFH histogram representing the feature at the query point
Definition at line 61 of file pfh.hpp.
References pcl::computePairFeatures(), pcl::isFinite(), and M_PI.
getMaximumCacheSize()
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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inline |
Get the maximum internal cache size.
Definition at line 123 of file pfh.h.
References pcl::PFHEstimation< PointInT, PointNT, PointOutT >::max_cache_size_.
getUseInternalCache()
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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inline |
Get whether the internal cache is used or not for computing the PFH features.
Definition at line 147 of file pfh.h.
References pcl::PFHEstimation< PointInT, PointNT, PointOutT >::use_cache_.
setMaximumCacheSize()
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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inline |
Set the maximum internal cache size.
Defaults to 2GB worth of entries.
- Parameters
-
[in] cache_size maximum cache size
Definition at line 116 of file pfh.h.
References pcl::PFHEstimation< PointInT, PointNT, PointOutT >::max_cache_size_.
setUseInternalCache()
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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inline |
Set whether to use an internal cache mechanism for removing redundant calculations or not.
- Note
- Depending on how the point cloud is ordered and how the nearest neighbors are estimated, using a cache could have a positive or a negative influence. Please test with and without a cache on your data, and choose whatever works best!
See setMaximumCacheSize for setting the maximum cache size
- Parameters
-
[in] use_cache set to true to use the internal cache, false otherwise
Definition at line 140 of file pfh.h.
References pcl::PFHEstimation< PointInT, PointNT, PointOutT >::use_cache_.
Member Data Documentation
d_pi_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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protected |
f_index_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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protected |
feature_map_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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protected |
key_list_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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protected |
max_cache_size_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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protected |
Maximum size of internal cache memory.
Definition at line 213 of file pfh.h.
Referenced by pcl::PFHEstimation< PointInT, PointNT, PointOutT >::getMaximumCacheSize(), and pcl::PFHEstimation< PointInT, PointNT, PointOutT >::setMaximumCacheSize().
nr_subdiv_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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protected |
pfh_histogram_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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protected |
pfh_tuple_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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protected |
use_cache_
template<typename PointInT , typename PointNT , typename PointOutT = pcl::PFHSignature125>
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protected |
Set to true to use the internal cache for removing redundant computations.
Definition at line 216 of file pfh.h.
Referenced by pcl::PFHEstimation< PointInT, PointNT, PointOutT >::getUseInternalCache(), and pcl::PFHEstimation< PointInT, PointNT, PointOutT >::setUseInternalCache().
The documentation for this class was generated from the following files:
© 2009–2012, Willow Garage, Inc.
© 2012–, Open Perception, Inc.
Licensed under the BSD License.
https://pointclouds.org/documentation/classpcl_1_1_p_f_h_estimation.html
