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using | Ptr = shared_ptr< CRHEstimation< PointInT, PointNT, PointOutT > > |
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using | ConstPtr = shared_ptr< const CRHEstimation< PointInT, PointNT, PointOutT > > |
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using | PointCloudOut = typename Feature< PointInT, PointOutT >::PointCloudOut |
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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::Histogram< 90 > > > |
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using | ConstPtr = shared_ptr< const FeatureFromNormals< PointInT, PointNT, pcl::Histogram< 90 > > > |
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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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virtual bool | initCompute () |
| 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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PointCloudNConstPtr | normals_ |
| A pointer to the input dataset that contains the point normals of the XYZ dataset. More...
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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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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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template<typename PointInT, typename PointNT, typename PointOutT = pcl::Histogram<90>>
class pcl::CRHEstimation< PointInT, PointNT, PointOutT >
CRHEstimation estimates the Camera Roll Histogram (CRH) descriptor for a given point cloud dataset containing XYZ data and normals, as presented in:
- CAD-Model Recognition and 6 DOF Pose Estimation A. Aldoma, N. Blodow, D. Gossow, S. Gedikli, R.B. Rusu, M. Vincze and G. Bradski ICCV 2011, 3D Representation and Recognition (3dRR11) workshop Barcelona, Spain, (2011)
The suggested PointOutT is pcl::Histogram<90>. //dc (real) + 44 complex numbers (real, imaginary) + nyquist (real)
- Author
- Aitor Aldoma
Definition at line 60 of file crh.h.