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Point Cloud Library (PCL)
1.4.0
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00001 /* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Copyright (c) 2009, Willow Garage, Inc. 00005 * All rights reserved. 00006 * 00007 * Redistribution and use in source and binary forms, with or without 00008 * modification, are permitted provided that the following conditions 00009 * are met: 00010 * 00011 * * Redistributions of source code must retain the above copyright 00012 * notice, this list of conditions and the following disclaimer. 00013 * * Redistributions in binary form must reproduce the above 00014 * copyright notice, this list of conditions and the following 00015 * disclaimer in the documentation and/or other materials provided 00016 * with the distribution. 00017 * * Neither the name of Willow Garage, Inc. nor the names of its 00018 * contributors may be used to endorse or promote products derived 00019 * from this software without specific prior written permission. 00020 * 00021 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00022 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00023 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00024 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00025 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00026 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00027 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00028 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00029 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00030 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00031 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00032 * POSSIBILITY OF SUCH DAMAGE. 00033 * 00034 * $Id: rsd.hpp 3755 2011-12-31 23:45:30Z rusu $ 00035 * 00036 */ 00037 00038 #ifndef PCL_FEATURES_IMPL_RSD_H_ 00039 #define PCL_FEATURES_IMPL_RSD_H_ 00040 00041 #include <cfloat> 00042 #include "pcl/features/rsd.h" 00043 00045 template <typename PointInT, typename PointNT, typename PointOutT> inline void 00046 pcl::computeRSD (const pcl::PointCloud<PointInT> &surface, const pcl::PointCloud<PointNT> &normals, 00047 const std::vector<int> &indices, double max_dist, 00048 int nr_subdiv, double plane_radius, PointOutT &radii, Eigen::MatrixXf *histogram) 00049 { 00050 // Check if the full histogram has to be saved or not 00051 if (histogram) 00052 *histogram = Eigen::MatrixXf::Zero (nr_subdiv, nr_subdiv); 00053 00054 // Initialize minimum and maximum angle values in each distance bin 00055 std::vector<std::vector<double> > min_max_angle_by_dist (nr_subdiv); 00056 min_max_angle_by_dist[0].resize (2); 00057 min_max_angle_by_dist[0][0] = min_max_angle_by_dist[0][1] = 0.0; 00058 for (int di=1; di<nr_subdiv; di++) 00059 { 00060 min_max_angle_by_dist[di].resize (2); 00061 min_max_angle_by_dist[di][0] = +DBL_MAX; 00062 min_max_angle_by_dist[di][1] = -DBL_MAX; 00063 } 00064 00065 // Compute distance by normal angle distribution for points 00066 std::vector<int>::const_iterator i, begin (indices.begin()), end (indices.end()); 00067 for(i = begin+1; i != end; ++i) 00068 { 00069 // compute angle between the two lines going through normals (disregard orientation!) 00070 double cosine = normals.points[*i].normal[0] * normals.points[*begin].normal[0] + 00071 normals.points[*i].normal[1] * normals.points[*begin].normal[1] + 00072 normals.points[*i].normal[2] * normals.points[*begin].normal[2]; 00073 if (cosine > 1) cosine = 1; 00074 if (cosine < -1) cosine = -1; 00075 double angle = acos (cosine); 00076 if (angle > M_PI/2) angle = M_PI - angle; 00077 00078 // Compute point to point distance 00079 double dist = sqrt ((surface.points[*i].x - surface.points[*begin].x) * (surface.points[*i].x - surface.points[*begin].x) + 00080 (surface.points[*i].y - surface.points[*begin].y) * (surface.points[*i].y - surface.points[*begin].y) + 00081 (surface.points[*i].z - surface.points[*begin].z) * (surface.points[*i].z - surface.points[*begin].z)); 00082 00083 if (dist > max_dist) 00084 continue; 00085 00086 // compute bins and increase 00087 int bin_d = (int) floor (nr_subdiv * dist / max_dist); 00088 if (histogram) 00089 { 00090 int bin_a = (int) floor (nr_subdiv * angle / (M_PI/2)); 00091 (*histogram)(bin_a, bin_d)++; 00092 } 00093 00094 // update min-max values for distance bins 00095 if (min_max_angle_by_dist[bin_d][0] > angle) min_max_angle_by_dist[bin_d][0] = angle; 00096 if (min_max_angle_by_dist[bin_d][1] < angle) min_max_angle_by_dist[bin_d][1] = angle; 00097 } 00098 00099 // Estimate radius from min and max lines 00100 double Amint_Amin = 0, Amint_d = 0; 00101 double Amaxt_Amax = 0, Amaxt_d = 0; 00102 for (int di=0; di<nr_subdiv; di++) 00103 { 00104 // combute the members of A'*A*r = A'*D 00105 if (min_max_angle_by_dist[di][1] >= 0) 00106 { 00107 double p_min = min_max_angle_by_dist[di][0]; 00108 double p_max = min_max_angle_by_dist[di][1]; 00109 double f = (di+0.5)*max_dist/nr_subdiv; 00110 Amint_Amin += p_min * p_min; 00111 Amint_d += p_min * f; 00112 Amaxt_Amax += p_max * p_max; 00113 Amaxt_d += p_max * f; 00114 } 00115 } 00116 float min_radius = Amint_Amin == 0 ? plane_radius : std::min (Amint_d/Amint_Amin, plane_radius); 00117 float max_radius = Amaxt_Amax == 0 ? plane_radius : std::min (Amaxt_d/Amaxt_Amax, plane_radius); 00118 00119 // Small correction of the systematic error of the estimation (based on analysis with nr_subdiv_ = 5) 00120 min_radius *= 1.1; 00121 max_radius *= 0.9; 00122 if (min_radius < max_radius) 00123 { 00124 radii.r_min = min_radius; 00125 radii.r_max = max_radius; 00126 } 00127 else 00128 { 00129 radii.r_max = min_radius; 00130 radii.r_min = max_radius; 00131 } 00132 } 00133 00135 template <typename PointInT, typename PointNT, typename PointOutT> void 00136 pcl::RSDEstimation<PointInT, PointNT, PointOutT>::computeFeature (PointCloudOut &output) 00137 { 00138 // Check if search_radius_ was set 00139 if (search_radius_ < 0) 00140 { 00141 PCL_ERROR ("[pcl::%s::computeFeature] A search radius needs to be set!\n", getClassName ().c_str ()); 00142 output.width = output.height = 0; 00143 output.points.clear (); 00144 return; 00145 } 00146 00147 // Allocate enough space to hold the results 00148 // \note resize is irrelevant for a radiusSearch (). 00149 std::vector<int> nn_indices; 00150 std::vector<float> nn_sqr_dists; 00151 00152 // Resize the output histogram dataset 00153 if (save_histograms_) 00154 histograms_.resize (output.points.size ()); 00155 00156 // Iterating over the entire index vector 00157 for (size_t idx = 0; idx < indices_->size (); ++idx) 00158 { 00159 // Compute and store r_min and r_max in the output cloud 00160 this->searchForNeighbors ((*indices_)[idx], search_parameter_, nn_indices, nn_sqr_dists); 00161 00162 // check if the full histogram has to be saved or not 00163 if (save_histograms_) 00164 computeRSD (*surface_, *normals_, nn_indices, search_radius_, nr_subdiv_, plane_radius_, output.points[idx], &(histograms_[idx])); 00165 else 00166 computeRSD (*surface_, *normals_, nn_indices, search_radius_, nr_subdiv_, plane_radius_, output.points[idx]); 00167 } 00168 } 00169 00170 #define PCL_INSTANTIATE_RSDEstimation(T,NT,OutT) template class PCL_EXPORTS pcl::RSDEstimation<T,NT,OutT>; 00171 00172 #endif // PCL_FEATURES_IMPL_VFH_H_
1.7.6.1