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Merge pull request #790 from desinghkar/grsd_request
Including GRSD a global radius-based surface descriptor
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| /* | ||
| * Software License Agreement (BSD License) | ||
| * | ||
| * Point Cloud Library (PCL) - www.pointclouds.org | ||
| * Copyright (c) 2009-2014, Willow Garage, Inc. | ||
| * Copyright (c) 2014-, Open Perception, Inc. | ||
| * | ||
| * All rights reserved. | ||
| * | ||
| * Redistribution and use in source and binary forms, with or without | ||
| * modification, are permitted provided that the following conditions | ||
| * are met: | ||
| * | ||
| * * Redistributions of source code must retain the above copyright | ||
| * notice, this list of conditions and the following disclaimer. | ||
| * * Redistributions in binary form must reproduce the above | ||
| * copyright notice, this list of conditions and the following | ||
| * disclaimer in the documentation and/or other materials provided | ||
| * with the distribution. | ||
| * * Neither the name of the copyright holder(s) nor the names of its | ||
| * contributors may be used to endorse or promote products derived | ||
| * from this software without specific prior written permission. | ||
| * | ||
| * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS | ||
| * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT | ||
| * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS | ||
| * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE | ||
| * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, | ||
| * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, | ||
| * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
| * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | ||
| * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT | ||
| * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN | ||
| * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | ||
| * POSSIBILITY OF SUCH DAMAGE. | ||
| * | ||
| */ | ||
|
|
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| #ifndef PCL_FEATURES_GRSD_H_ | ||
| #define PCL_FEATURES_GRSD_H_ | ||
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| #include <pcl/features/feature.h> | ||
| #include <pcl/features/rsd.h> | ||
| #include <pcl/filters/voxel_grid.h> | ||
| #include <pcl/kdtree/kdtree_flann.h> | ||
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| namespace pcl | ||
| { | ||
| /** \brief @b GRSDEstimation estimates the Global Radius-based Surface Descriptor (GRSD) for a given point cloud dataset | ||
| * containing points and normals. | ||
| * | ||
| * @note If you use this code in any academic work, please cite (first for the ray-casting and second for the additive version): | ||
| * | ||
| * <ul> | ||
| * <li> Z.C. Marton, D. Pangercic, N. Blodow, Michael Beetz. | ||
| * Combined 2D-3D Categorization and Classification for Multimodal Perception Systems. | ||
| * In The International Journal of Robotics Research, Sage Publications | ||
| * pages 1378--1402, Volume 30, Number 11, September 2011. | ||
| * </li> | ||
| * <li> A. Kanezaki, Z.C. Marton, D. Pangercic, T. Harada, Y. Kuniyoshi, M. Beetz. | ||
| * Voxelized Shape and Color Histograms for RGB-D | ||
| * In the Workshop on Active Semantic Perception and Object Search in the Real World, in conjunction with the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) | ||
| * San Francisco, California, September 25-30, 2011. | ||
| * </li> | ||
| * </ul> | ||
| * | ||
| * @note The code is stateful as we do not expect this class to be multicore parallelized. Please look at | ||
| * \ref FPFHEstimationOMP for examples on parallel implementations of the FPFH (Fast Point Feature Histogram). | ||
| * \author Zoltan Csaba Marton | ||
| * \ingroup features | ||
| */ | ||
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| template <typename PointInT, typename PointNT, typename PointOutT> | ||
| class GRSDEstimation : public FeatureFromNormals<PointInT, PointNT, PointOutT> | ||
| { | ||
| public: | ||
| using Feature<PointInT, PointOutT>::feature_name_; | ||
| using Feature<PointInT, PointOutT>::getClassName; | ||
| using Feature<PointInT, PointOutT>::indices_; | ||
| using Feature<PointInT, PointOutT>::search_radius_; | ||
| using Feature<PointInT, PointOutT>::search_parameter_; | ||
| using Feature<PointInT, PointOutT>::input_; | ||
| using FeatureFromNormals<PointInT, PointNT, PointOutT>::normals_; | ||
| using Feature<PointInT, PointOutT>::setSearchSurface; | ||
| //using Feature<PointInT, PointOutT>::computeFeature; | ||
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| typedef typename Feature<PointInT, PointOutT>::PointCloudOut PointCloudOut; | ||
| typedef typename Feature<PointInT, PointOutT>::PointCloudIn PointCloudIn; | ||
| typedef typename Feature<PointInT, PointOutT>::PointCloudInPtr PointCloudInPtr; | ||
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| /** \brief Constructor. */ | ||
| GRSDEstimation () : additive_ (true) | ||
| { | ||
| feature_name_ = "GRSDEstimation"; | ||
| relative_coordinates_all_ = getAllNeighborCellIndices (); | ||
| }; | ||
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| /** \brief Set the sphere radius that is to be used for determining the nearest neighbors used for the feature | ||
| * estimation. Same value will be used for the internal voxel grid leaf size. | ||
| * \param[in] radius the sphere radius used as the maximum distance to consider a point a neighbor | ||
| */ | ||
| inline void | ||
| setRadiusSearch (double radius) { width_ = search_radius_ = radius; } | ||
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| /** \brief Get the sphere radius used for determining the neighbors. | ||
| * \return the sphere radius used as the maximum distance to consider a point a neighbor | ||
| */ | ||
| inline double | ||
| getRadiusSearch () const { return (search_radius_); } | ||
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| /** \brief Get the type of the local surface based on the min and max radius computed. | ||
| * \return the integer that represents the type of the local surface with values as | ||
| * Plane (1), Cylinder (2), Noise or corner (0), Sphere (3) and Edge (4) | ||
| */ | ||
| static inline int | ||
| getSimpleType (float min_radius, float max_radius, double min_radius_plane, double max_radius_noise, | ||
| double min_radius_cylinder, double max_min_radius_diff); | ||
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| protected: | ||
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| /** \brief Estimate the Global Radius-based Surface Descriptor (GRSD) for a set of points given by | ||
| * <setInputCloud (), setIndices ()> using the surface in setSearchSurface () and the spatial locator in | ||
| * setSearchMethod () | ||
| * \param output the resultant point cloud that contains the GRSD feature | ||
| */ | ||
| void | ||
| computeFeature (PointCloudOut &output); | ||
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| private: | ||
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| /** \brief Defines if an additive feature is computed or ray-casting is used to get a more descriptive feature. */ | ||
| bool additive_; | ||
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| /** \brief Defines the voxel size to be used. */ | ||
| double width_; | ||
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| /** \brief Pre-computed the relative cell indices of all the 26 neighbors. */ | ||
| Eigen::MatrixXi relative_coordinates_all_; | ||
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| }; | ||
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| } | ||
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| #ifdef PCL_NO_PRECOMPILE | ||
| #include <pcl/features/impl/grsd.hpp> | ||
| #endif | ||
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| #endif /* PCL_FEATURES_GRSD_H_ */ |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,130 @@ | ||
| /* | ||
| * Software License Agreement (BSD License) | ||
| * | ||
| * Point Cloud Library (PCL) - www.pointclouds.org | ||
| * Copyright (c) 2009-2014, Willow Garage, Inc. | ||
| * Copyright (c) 2014-, Open Perception, Inc. | ||
| * | ||
| * All rights reserved. | ||
| * | ||
| * Redistribution and use in source and binary forms, with or without | ||
| * modification, are permitted provided that the following conditions | ||
| * are met: | ||
| * | ||
| * * Redistributions of source code must retain the above copyright | ||
| * notice, this list of conditions and the following disclaimer. | ||
| * * Redistributions in binary form must reproduce the above | ||
| * copyright notice, this list of conditions and the following | ||
| * disclaimer in the documentation and/or other materials provided | ||
| * with the distribution. | ||
| * * Neither the name of the copyright holder(s) nor the names of its | ||
| * contributors may be used to endorse or promote products derived | ||
| * from this software without specific prior written permission. | ||
| * | ||
| * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS | ||
| * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT | ||
| * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS | ||
| * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE | ||
| * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, | ||
| * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, | ||
| * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
| * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | ||
| * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT | ||
| * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN | ||
| * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | ||
| * POSSIBILITY OF SUCH DAMAGE. | ||
| * | ||
| */ | ||
|
|
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| #ifndef PCL_FEATURES_IMPL_GRSD_H_ | ||
| #define PCL_FEATURES_IMPL_GRSD_H_ | ||
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| #include <pcl/features/grsd.h> | ||
| ///////// STATIC ///////// | ||
| template <typename PointInT, typename PointNT, typename PointOutT> int | ||
| pcl::GRSDEstimation<PointInT, PointNT, PointOutT>::getSimpleType (float min_radius, float max_radius, | ||
| double min_radius_plane = 0.100, | ||
| double max_radius_noise = 0.015, | ||
| double min_radius_cylinder = 0.175, | ||
| double max_min_radius_diff = 0.050) | ||
| { | ||
| if (min_radius > min_radius_plane) | ||
| return (1); // plane | ||
| else if (max_radius > min_radius_cylinder) | ||
| return (2); // cylinder (rim) | ||
| else if (min_radius < max_radius_noise) | ||
| return (0); // noise/corner | ||
| else if (max_radius - min_radius < max_min_radius_diff) | ||
| return (3); // sphere/corner | ||
| else | ||
| return (4); // edge | ||
| } | ||
|
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| ////////////////////////////////////////////////////////////////////////////////////////////// | ||
| template <typename PointInT, typename PointNT, typename PointOutT> void | ||
| pcl::GRSDEstimation<PointInT, PointNT, PointOutT>::computeFeature (PointCloudOut &output) | ||
| { | ||
| // Check if search_radius_ was set | ||
| if (width_ < 0) | ||
| { | ||
| PCL_ERROR ("[pcl::%s::computeFeature] A voxel cell width needs to be set!\n", getClassName ().c_str ()); | ||
| output.width = output.height = 0; | ||
| output.points.clear (); | ||
| return; | ||
| } | ||
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| // Create the voxel grid | ||
| PointCloudInPtr cloud_downsampled (new PointCloudIn()); | ||
| pcl::VoxelGrid<PointInT> grid; | ||
| grid.setLeafSize (width_, width_, width_); | ||
| grid.setInputCloud (input_); | ||
| grid.setSaveLeafLayout (true); // TODO maybe avoid this using nearest neighbor search | ||
| grid.filter (*cloud_downsampled); | ||
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| // Compute RSD | ||
| pcl::PointCloud<pcl::PrincipalRadiiRSD>::Ptr radii (new pcl::PointCloud<pcl::PrincipalRadiiRSD>()); | ||
| pcl::RSDEstimation<PointInT, PointNT, pcl::PrincipalRadiiRSD> rsd; | ||
| rsd.setInputCloud (cloud_downsampled); | ||
| rsd.setSearchSurface (input_); | ||
| rsd.setInputNormals (normals_); | ||
| rsd.setRadiusSearch (std::max (search_radius_, sqrt (3) * width_ / 2)); | ||
| // pcl::KdTree<PointInT>::Ptr tree = boost::make_shared<pcl::KdTreeFLANN<PointInT> >(); | ||
| // tree->setInputCloud(input_); | ||
| // rsd.setSearchMethod(tree); | ||
| rsd.compute (*radii); | ||
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| // Save the type of each point | ||
| int NR_CLASS = 5; // TODO make this nicer | ||
| std::vector<int> types (radii->points.size ()); | ||
| for (size_t idx = 0; idx < radii->points.size (); ++idx) | ||
| types[idx] = getSimpleType (radii->points[idx].r_min, radii->points[idx].r_max); | ||
|
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| // Get the transitions between surface types between neighbors of occupied cells | ||
| Eigen::MatrixXi transition_matrix = Eigen::MatrixXi::Zero (NR_CLASS + 1, NR_CLASS + 1); | ||
| for (size_t idx = 0; idx < cloud_downsampled->points.size (); ++idx) | ||
| { | ||
| int source_type = types[idx]; | ||
| std::vector<int> neighbors = grid.getNeighborCentroidIndices (cloud_downsampled->points[idx], relative_coordinates_all_); | ||
| for (unsigned id_n = 0; id_n < neighbors.size (); id_n++) | ||
| { | ||
| int neighbor_type; | ||
| if (neighbors[id_n] == -1) // empty | ||
| neighbor_type = NR_CLASS; | ||
| else | ||
| neighbor_type = types[neighbors[id_n]]; | ||
| transition_matrix (source_type, neighbor_type)++; | ||
| } | ||
| } | ||
|
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| // Save feature values | ||
| output.points.resize (1); | ||
| output.height = output.width = 1; | ||
| int nrf = 0; | ||
| for (int i = 0; i < NR_CLASS + 1; i++) | ||
| for (int j = i; j < NR_CLASS + 1; j++) | ||
| output.points[0].histogram[nrf++] = transition_matrix (i, j) + transition_matrix (j, i); | ||
| } | ||
|
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| #define PCL_INSTANTIATE_GRSDEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::GRSDEstimation<T,NT,OutT>; | ||
|
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| #endif /* PCL_FEATURES_IMPL_GRSD_H_ */ |
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