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Point Cloud Library (PCL)
1.6.0
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00001 /* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Point Cloud Library (PCL) - www.pointclouds.org 00005 * Copyright (c) 2012, Open Perception, Inc. 00006 * 00007 * All rights reserved. 00008 * 00009 * Redistribution and use in source and binary forms, with or without 00010 * modification, are permitted provided that the following conditions 00011 * are met: 00012 * 00013 * * Redistributions of source code must retain the above copyright 00014 * notice, this list of conditions and the following disclaimer. 00015 * * Redistributions in binary form must reproduce the above 00016 * copyright notice, this list of conditions and the following 00017 * disclaimer in the documentation and/or other materials provided 00018 * with the distribution. 00019 * * Neither the name of Open Perception, Inc. nor the names of its 00020 * contributors may be used to endorse or promote products derived 00021 * from this software without specific prior written permission. 00022 * 00023 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00024 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00025 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00026 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00027 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00028 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00029 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00030 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00031 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00032 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00033 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00034 * POSSIBILITY OF SUCH DAMAGE. 00035 * 00036 * 00037 */ 00038 #ifndef PCL_REGISTRATION_IMPL_CORRESPONDENCE_REJECTION_VAR_TRIMMED_HPP_ 00039 #define PCL_REGISTRATION_IMPL_CORRESPONDENCE_REJECTION_VAR_TRIMMED_HPP_ 00040 00041 #include <vector> 00042 #include <algorithm> 00043 00045 void 00046 pcl::registration::CorrespondenceRejectorVarTrimmed::getRemainingCorrespondences ( 00047 const pcl::Correspondences& original_correspondences, 00048 pcl::Correspondences& remaining_correspondences) 00049 { 00050 std::vector <double> dists; 00051 dists.resize (original_correspondences.size ()); 00052 00053 for (size_t i = 0; i < original_correspondences.size (); ++i) 00054 { 00055 if (data_container_) 00056 { 00057 dists[i] = data_container_->getCorrespondenceScore (original_correspondences[i]); 00058 } 00059 else 00060 { 00061 dists[i] = original_correspondences[i].distance; 00062 } 00063 } 00064 factor_ = optimizeInlierRatio (dists); 00065 nth_element (dists.begin (), dists.begin () + int (dists.size () * factor_), dists.end ()); 00066 trimmed_distance_ = dists [int (dists.size () * factor_)]; 00067 00068 unsigned int number_valid_correspondences = 0; 00069 remaining_correspondences.resize (original_correspondences.size ()); 00070 00071 for (size_t i = 0; i < original_correspondences.size (); ++i) 00072 { 00073 if ( dists[i] < trimmed_distance_) 00074 { 00075 remaining_correspondences[number_valid_correspondences] = original_correspondences[i]; 00076 ++number_valid_correspondences; 00077 } 00078 } 00079 remaining_correspondences.resize (number_valid_correspondences); 00080 } 00081 00083 float 00084 pcl::registration::CorrespondenceRejectorVarTrimmed::optimizeInlierRatio (std::vector <double>& dists) 00085 { 00086 unsigned int points_nbr = dists.size (); 00087 std::sort (dists.begin (), dists.end ()); 00088 00089 const int min_el = int (floor (min_ratio_ * points_nbr)); 00090 const int max_el = int (floor (max_ratio_ * points_nbr)); 00091 00092 typedef Eigen::Array <double, Eigen::Dynamic, 1> LineArray; 00093 Eigen::Map<LineArray> sorted_dist (&dists[0], points_nbr); 00094 00095 const LineArray trunk_sorted_dist = sorted_dist.segment (min_el, max_el-min_el); 00096 const double lower_sum = sorted_dist.head (min_el).sum (); 00097 const LineArray ids = LineArray::LinSpaced (trunk_sorted_dist.rows (), min_el+1, max_el); 00098 const LineArray ratio = ids / points_nbr; 00099 const LineArray deno = ratio.pow (lambda_); 00100 const LineArray FRMS = deno.inverse ().square () * ids.inverse () * (lower_sum + trunk_sorted_dist); 00101 int min_index (0); 00102 FRMS.minCoeff (&min_index); 00103 00104 const float opt_ratio = float (min_index + min_el) / float (points_nbr); 00105 return opt_ratio; 00106 } 00107 00108 #endif /* PCL_REGISTRATION_IMPL_CORRESPONDENCE_REJECTION_VAR_TRIMMED_HPP_ */
1.7.6.1