Point Cloud Library (PCL)
1.7.0
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00001 /* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Point Cloud Library (PCL) - www.pointclouds.org 00005 * Copyright (c) 2009, Willow Garage, Inc. 00006 * Copyright (c) 2012-, Open Perception, Inc. 00007 * 00008 * All rights reserved. 00009 * 00010 * Redistribution and use in source and binary forms, with or without 00011 * modification, are permitted provided that the following conditions 00012 * are met: 00013 * 00014 * * Redistributions of source code must retain the above copyright 00015 * notice, this list of conditions and the following disclaimer. 00016 * * Redistributions in binary form must reproduce the above 00017 * copyright notice, this list of conditions and the following 00018 * disclaimer in the documentation and/or other materials provided 00019 * with the distribution. 00020 * * Neither the name of the copyright holder(s) nor the names of its 00021 * contributors may be used to endorse or promote products derived 00022 * from this software without specific prior written permission. 00023 * 00024 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00025 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00026 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00027 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00028 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00029 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00030 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00031 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00032 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00033 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00034 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00035 * POSSIBILITY OF SUCH DAMAGE. 00036 * 00037 * $Id$ 00038 * 00039 */ 00040 00041 #ifndef PCL_SAMPLE_CONSENSUS_IMPL_RRANSAC_H_ 00042 #define PCL_SAMPLE_CONSENSUS_IMPL_RRANSAC_H_ 00043 00044 #include <pcl/sample_consensus/rransac.h> 00045 00046 ////////////////////////////////////////////////////////////////////////// 00047 template <typename PointT> bool 00048 pcl::RandomizedRandomSampleConsensus<PointT>::computeModel (int debug_verbosity_level) 00049 { 00050 // Warn and exit if no threshold was set 00051 if (threshold_ == std::numeric_limits<double>::max()) 00052 { 00053 PCL_ERROR ("[pcl::RandomizedRandomSampleConsensus::computeModel] No threshold set!\n"); 00054 return (false); 00055 } 00056 00057 iterations_ = 0; 00058 int n_best_inliers_count = -INT_MAX; 00059 double k = 1.0; 00060 00061 std::vector<int> selection; 00062 Eigen::VectorXf model_coefficients; 00063 std::set<int> indices_subset; 00064 00065 int n_inliers_count = 0; 00066 unsigned skipped_count = 0; 00067 // supress infinite loops by just allowing 10 x maximum allowed iterations for invalid model parameters! 00068 const unsigned max_skip = max_iterations_ * 10; 00069 00070 // Number of samples to try randomly 00071 size_t fraction_nr_points = pcl_lrint (static_cast<double>(sac_model_->getIndices ()->size ()) * fraction_nr_pretest_ / 100.0); 00072 00073 // Iterate 00074 while (iterations_ < k && skipped_count < max_skip) 00075 { 00076 // Get X samples which satisfy the model criteria 00077 sac_model_->getSamples (iterations_, selection); 00078 00079 if (selection.empty ()) break; 00080 00081 // Search for inliers in the point cloud for the current plane model M 00082 if (!sac_model_->computeModelCoefficients (selection, model_coefficients)) 00083 { 00084 //iterations_++; 00085 ++ skipped_count; 00086 continue; 00087 } 00088 00089 // RRANSAC addon: verify a random fraction of the data 00090 // Get X random samples which satisfy the model criterion 00091 this->getRandomSamples (sac_model_->getIndices (), fraction_nr_points, indices_subset); 00092 if (!sac_model_->doSamplesVerifyModel (indices_subset, model_coefficients, threshold_)) 00093 { 00094 // Unfortunately we cannot "continue" after the first iteration, because k might not be set, while iterations gets incremented 00095 if (k > 1.0) 00096 { 00097 ++iterations_; 00098 continue; 00099 } 00100 } 00101 00102 // Select the inliers that are within threshold_ from the model 00103 n_inliers_count = sac_model_->countWithinDistance (model_coefficients, threshold_); 00104 00105 // Better match ? 00106 if (n_inliers_count > n_best_inliers_count) 00107 { 00108 n_best_inliers_count = n_inliers_count; 00109 00110 // Save the current model/inlier/coefficients selection as being the best so far 00111 model_ = selection; 00112 model_coefficients_ = model_coefficients; 00113 00114 // Compute the k parameter (k=log(z)/log(1-w^n)) 00115 double w = static_cast<double> (n_inliers_count) / static_cast<double> (sac_model_->getIndices ()->size ()); 00116 double p_no_outliers = 1 - pow (w, static_cast<double> (selection.size ())); 00117 p_no_outliers = (std::max) (std::numeric_limits<double>::epsilon (), p_no_outliers); // Avoid division by -Inf 00118 p_no_outliers = (std::min) (1 - std::numeric_limits<double>::epsilon (), p_no_outliers); // Avoid division by 0. 00119 k = log (1 - probability_) / log (p_no_outliers); 00120 } 00121 00122 ++iterations_; 00123 00124 if (debug_verbosity_level > 1) 00125 PCL_DEBUG ("[pcl::RandomizedRandomSampleConsensus::computeModel] Trial %d out of %d: %d inliers (best is: %d so far).\n", iterations_, static_cast<int> (ceil (k)), n_inliers_count, n_best_inliers_count); 00126 if (iterations_ > max_iterations_) 00127 { 00128 if (debug_verbosity_level > 0) 00129 PCL_DEBUG ("[pcl::RandomizedRandomSampleConsensus::computeModel] RRANSAC reached the maximum number of trials.\n"); 00130 break; 00131 } 00132 } 00133 00134 if (debug_verbosity_level > 0) 00135 PCL_DEBUG ("[pcl::RandomizedRandomSampleConsensus::computeModel] Model: %zu size, %d inliers.\n", model_.size (), n_best_inliers_count); 00136 00137 if (model_.empty ()) 00138 { 00139 inliers_.clear (); 00140 return (false); 00141 } 00142 00143 // Get the set of inliers that correspond to the best model found so far 00144 sac_model_->selectWithinDistance (model_coefficients_, threshold_, inliers_); 00145 return (true); 00146 } 00147 00148 #define PCL_INSTANTIATE_RandomizedRandomSampleConsensus(T) template class PCL_EXPORTS pcl::RandomizedRandomSampleConsensus<T>; 00149 00150 #endif // PCL_SAMPLE_CONSENSUS_IMPL_RRANSAC_H_ 00151