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using | PointCloudOut = typename Feature< PointInT, PointOutT >::PointCloudOut |
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using | Ptr = shared_ptr< VFHEstimation< PointInT, PointNT, PointOutT > > |
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using | ConstPtr = shared_ptr< const VFHEstimation< PointInT, PointNT, PointOutT > > |
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using | PointCloudN = pcl::PointCloud< PointNT > |
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using | PointCloudNPtr = typename PointCloudN::Ptr |
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using | PointCloudNConstPtr = typename PointCloudN::ConstPtr |
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using | Ptr = shared_ptr< FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 > > |
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using | ConstPtr = shared_ptr< const FeatureFromNormals< PointInT, PointNT, pcl::VFHSignature308 > > |
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using | BaseClass = PCLBase< PointInT > |
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using | Ptr = shared_ptr< Feature< PointInT, PointOutT > > |
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using | ConstPtr = shared_ptr< const Feature< PointInT, PointOutT > > |
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using | KdTree = pcl::search::Search< PointInT > |
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using | KdTreePtr = typename KdTree::Ptr |
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using | PointCloudIn = pcl::PointCloud< PointInT > |
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using | PointCloudInPtr = typename PointCloudIn::Ptr |
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using | PointCloudInConstPtr = typename PointCloudIn::ConstPtr |
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using | PointCloudOut = pcl::PointCloud< PointOutT > |
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using | SearchMethod = std::function< int(std::size_t, double, pcl::Indices &, std::vector< float > &)> |
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using | SearchMethodSurface = std::function< int(const PointCloudIn &cloud, std::size_t index, double, pcl::Indices &, std::vector< float > &)> |
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using | PointCloud = pcl::PointCloud< PointInT > |
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using | PointCloudPtr = typename PointCloud::Ptr |
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using | PointCloudConstPtr = typename PointCloud::ConstPtr |
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using | PointIndicesPtr = PointIndices::Ptr |
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using | PointIndicesConstPtr = PointIndices::ConstPtr |
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| VFHEstimation () |
| Empty constructor. More...
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void | computePointSPFHSignature (const Eigen::Vector4f ¢roid_p, const Eigen::Vector4f ¢roid_n, const pcl::PointCloud< PointInT > &cloud, const pcl::PointCloud< PointNT > &normals, const pcl::Indices &indices) |
| Estimate the SPFH (Simple Point Feature Histograms) signatures of the angular (f1, f2, f3) and distance (f4) features for a given point from its neighborhood. More...
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void | setViewPoint (float vpx, float vpy, float vpz) |
| Set the viewpoint. More...
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void | getViewPoint (float &vpx, float &vpy, float &vpz) |
| Get the viewpoint. More...
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void | setUseGivenNormal (bool use) |
| Set use_given_normal_. More...
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void | setNormalToUse (const Eigen::Vector3f &normal) |
| Set the normal to use. More...
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void | setUseGivenCentroid (bool use) |
| Set use_given_centroid_. More...
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void | setCentroidToUse (const Eigen::Vector3f ¢roid) |
| Set centroid_to_use_. More...
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void | setNormalizeBins (bool normalize) |
| set normalize_bins_ More...
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void | setNormalizeDistance (bool normalize) |
| set normalize_distances_ More...
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void | setFillSizeComponent (bool fill_size) |
| set size_component_ More...
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void | compute (PointCloudOut &output) |
| Overloaded computed method from pcl::Feature. More...
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| FeatureFromNormals () |
| Empty constructor. 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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| Feature () |
| Empty constructor. 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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| 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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PointCloudConstPtr const | 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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IndicesConstPtr const | 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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bool | initCompute () override |
| This method should get called before starting the actual computation. More...
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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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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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template<typename PointInT, typename PointNT, typename PointOutT = pcl::VFHSignature308>
class pcl::VFHEstimation< PointInT, PointNT, PointOutT >
VFHEstimation estimates the Viewpoint Feature Histogram (VFH) descriptor for a given point cloud dataset containing points and normals.
The default VFH implementation uses 45 binning subdivisions for each of the three extended FPFH values, plus another 45 binning subdivisions for the distances between each point and the centroid and 128 binning subdivisions for the viewpoint component, which results in a 308-byte array of float values. These are stored in a pcl::VFHSignature308 point type. A major difference between the PFH/FPFH descriptors and VFH, is that for a given point cloud dataset, only a single VFH descriptor will be estimated (vfhs->size() should be 1), while the resultant PFH/FPFH data will have the same number of entries as the number of points in the cloud.
- Note
- If you use this code in any academic work, please cite:
- R.B. Rusu, G. Bradski, R. Thibaux, J. Hsu. Fast 3D Recognition and Pose Using the Viewpoint Feature Histogram. In Proceedings of International Conference on Intelligent Robots and Systems (IROS) Taipei, Taiwan, October 18-22 2010.
- Note
- The code is stateful as we do not expect this class to be multicore parallelized. Please look at FPFHEstimationOMP for an example of a parallel implementation of the FPFH (Fast Point Feature Histogram).
- Author
- Radu B. Rusu
Definition at line 72 of file vfh.h.