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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) 2010-2011, Willow Garage, 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 Willow Garage, 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 00039 #ifndef PCL_REGISTRATION_CORRESPONDENCE_REJECTION_H_ 00040 #define PCL_REGISTRATION_CORRESPONDENCE_REJECTION_H_ 00041 00042 #include <pcl/registration/correspondence_types.h> 00043 #include <pcl/registration/correspondence_sorting.h> 00044 #include <pcl/console/print.h> 00045 #include <pcl/point_cloud.h> 00046 #include <pcl/kdtree/kdtree_flann.h> 00047 00048 namespace pcl 00049 { 00050 namespace registration 00051 { 00056 class CorrespondenceRejector 00057 { 00058 public: 00060 CorrespondenceRejector () : rejection_name_ (), input_correspondences_ () {}; 00061 00063 virtual ~CorrespondenceRejector () {} 00064 00068 virtual inline void 00069 setInputCorrespondences (const CorrespondencesConstPtr &correspondences) 00070 { 00071 input_correspondences_ = correspondences; 00072 }; 00073 00077 inline CorrespondencesConstPtr 00078 getInputCorrespondences () { return input_correspondences_; }; 00079 00083 inline void 00084 getCorrespondences (pcl::Correspondences &correspondences) 00085 { 00086 if (!input_correspondences_ || (input_correspondences_->empty ())) 00087 return; 00088 00089 applyRejection (correspondences); 00090 } 00091 00099 virtual inline void 00100 getRemainingCorrespondences (const pcl::Correspondences& original_correspondences, 00101 pcl::Correspondences& remaining_correspondences) = 0; 00102 00111 inline void 00112 getRejectedQueryIndices (const pcl::Correspondences &correspondences, 00113 std::vector<int>& indices) 00114 { 00115 if (!input_correspondences_ || input_correspondences_->empty ()) 00116 { 00117 PCL_WARN ("[pcl::%s::getRejectedQueryIndices] Input correspondences not set (lookup of rejected correspondences _not_ possible).\n", getClassName ().c_str ()); 00118 return; 00119 } 00120 00121 pcl::getRejectedQueryIndices(*input_correspondences_, correspondences, indices); 00122 } 00123 00124 protected: 00125 00127 std::string rejection_name_; 00128 00130 CorrespondencesConstPtr input_correspondences_; 00131 00133 inline const std::string& 00134 getClassName () const { return (rejection_name_); } 00135 00137 virtual void 00138 applyRejection (Correspondences &correspondences) = 0; 00139 }; 00140 00145 class DataContainerInterface 00146 { 00147 public: 00148 virtual ~DataContainerInterface () {} 00149 virtual double getCorrespondenceScore (int index) = 0; 00150 virtual double getCorrespondenceScore (const pcl::Correspondence &) = 0; 00151 }; 00152 00157 template <typename PointT, typename NormalT=pcl::PointNormal> 00158 class DataContainer : public DataContainerInterface 00159 { 00160 typedef typename pcl::PointCloud<PointT>::ConstPtr PointCloudConstPtr; 00161 typedef typename pcl::KdTree<PointT>::Ptr KdTreePtr; 00162 typedef typename pcl::PointCloud<NormalT>::ConstPtr NormalsPtr; 00163 00164 public: 00165 00167 DataContainer () : input_ (), target_ () 00168 { 00169 tree_.reset (new pcl::KdTreeFLANN<PointT>); 00170 } 00171 00176 inline void 00177 setInputCloud (const PointCloudConstPtr &cloud) 00178 { 00179 input_ = cloud; 00180 } 00181 00186 inline void 00187 setInputTarget (const PointCloudConstPtr &target) 00188 { 00189 target_ = target; 00190 tree_->setInputCloud (target_); 00191 } 00192 00196 inline void 00197 setInputNormals (const NormalsPtr &normals) { input_normals_ = normals; } 00198 00202 inline void 00203 setTargetNormals (const NormalsPtr &normals) { target_normals_ = normals; } 00204 00206 inline NormalsPtr 00207 getInputNormals () { return input_normals_; } 00208 00210 inline NormalsPtr 00211 getTargetNormals () { return target_normals_; } 00212 00216 inline double 00217 getCorrespondenceScore (int index) 00218 { 00219 std::vector<int> indices (1); 00220 std::vector<float> distances (1); 00221 if (tree_->nearestKSearch (input_->points[index], 1, indices, distances)) 00222 { 00223 return (distances[0]); 00224 } 00225 else 00226 return (std::numeric_limits<double>::max ()); 00227 } 00228 00232 inline double 00233 getCorrespondenceScore (const pcl::Correspondence &corr) 00234 { 00235 // Get the source and the target feature from the list 00236 const PointT &src = input_->points[corr.index_query]; 00237 const PointT &tgt = target_->points[corr.index_match]; 00238 00239 return ((src.getVector4fMap () - tgt.getVector4fMap ()).squaredNorm ()); 00240 } 00241 00247 double 00248 getCorrespondenceScoreFromNormals (const pcl::Correspondence &corr) 00249 { 00250 //assert ( (input_normals_->points.size () != 0) && (target_normals_->points.size () != 0) && "Normals are not set for the input and target point clouds"); 00251 assert ( input_normals_ && target_normals_ && "Normals are not set for the input and target point clouds"); 00252 const NormalT &src = input_normals_->points[corr.index_query]; 00253 const NormalT &tgt = target_normals_->points[corr.index_match]; 00254 double score = (src.normal[0] * tgt.normal[0]) + (src.normal[1] * tgt.normal[1]) + (src.normal[2] * tgt.normal[2]); 00255 return score; 00256 } 00257 private: 00258 00260 PointCloudConstPtr input_; 00261 00263 PointCloudConstPtr target_; 00264 00266 NormalsPtr input_normals_; 00267 00269 NormalsPtr target_normals_; 00270 00272 KdTreePtr tree_; 00273 }; 00274 } 00275 } 00276 00277 #endif /* PCL_REGISTRATION_CORRESPONDENCE_REJECTION_H_ */ 00278
1.7.6.1