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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) 2009-2011, 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 * $Id: kdtree.h 6121 2012-07-03 18:53:38Z aichim $ 00037 * 00038 */ 00039 00040 #ifndef PCL_KDTREE_KDTREE_H_ 00041 #define PCL_KDTREE_KDTREE_H_ 00042 00043 #include <limits.h> 00044 #include <pcl/pcl_macros.h> 00045 #include <pcl/point_cloud.h> 00046 #include <pcl/point_representation.h> 00047 #include <pcl/common/io.h> 00048 00049 namespace pcl 00050 { 00055 template <typename PointT> 00056 class KdTree 00057 { 00058 public: 00059 typedef boost::shared_ptr <std::vector<int> > IndicesPtr; 00060 typedef boost::shared_ptr <const std::vector<int> > IndicesConstPtr; 00061 00062 typedef pcl::PointCloud<PointT> PointCloud; 00063 typedef boost::shared_ptr<PointCloud> PointCloudPtr; 00064 typedef boost::shared_ptr<const PointCloud> PointCloudConstPtr; 00065 00066 typedef pcl::PointRepresentation<PointT> PointRepresentation; 00067 //typedef boost::shared_ptr<PointRepresentation> PointRepresentationPtr; 00068 typedef boost::shared_ptr<const PointRepresentation> PointRepresentationConstPtr; 00069 00070 // Boost shared pointers 00071 typedef boost::shared_ptr<KdTree<PointT> > Ptr; 00072 typedef boost::shared_ptr<const KdTree<PointT> > ConstPtr; 00073 00077 KdTree (bool sorted = true) : input_(), indices_(), 00078 epsilon_(0.0f), min_pts_(1), sorted_(sorted), 00079 point_representation_ (new DefaultPointRepresentation<PointT>) 00080 { 00081 }; 00082 00087 virtual void 00088 setInputCloud (const PointCloudConstPtr &cloud, const IndicesConstPtr &indices = IndicesConstPtr ()) 00089 { 00090 input_ = cloud; 00091 indices_ = indices; 00092 } 00093 00095 inline IndicesConstPtr 00096 getIndices () const 00097 { 00098 return (indices_); 00099 } 00100 00102 inline PointCloudConstPtr 00103 getInputCloud () const 00104 { 00105 return (input_); 00106 } 00107 00111 inline void 00112 setPointRepresentation (const PointRepresentationConstPtr &point_representation) 00113 { 00114 point_representation_ = point_representation; 00115 setInputCloud (input_, indices_); // Makes sense in derived classes to reinitialize the tree 00116 } 00117 00119 inline PointRepresentationConstPtr 00120 getPointRepresentation () const 00121 { 00122 return (point_representation_); 00123 } 00124 00126 virtual ~KdTree () {}; 00127 00136 virtual int 00137 nearestKSearch (const PointT &p_q, int k, 00138 std::vector<int> &k_indices, std::vector<float> &k_sqr_distances) const = 0; 00139 00156 virtual int 00157 nearestKSearch (const PointCloud &cloud, int index, int k, 00158 std::vector<int> &k_indices, std::vector<float> &k_sqr_distances) const 00159 { 00160 assert (index >= 0 && index < static_cast<int> (cloud.points.size ()) && "Out-of-bounds error in nearestKSearch!"); 00161 return (nearestKSearch (cloud.points[index], k, k_indices, k_sqr_distances)); 00162 } 00163 00173 template <typename PointTDiff> inline int 00174 nearestKSearchT (const PointTDiff &point, int k, 00175 std::vector<int> &k_indices, std::vector<float> &k_sqr_distances) const 00176 { 00177 PointT p; 00178 // Copy all the data fields from the input cloud to the output one 00179 typedef typename pcl::traits::fieldList<PointT>::type FieldListInT; 00180 typedef typename pcl::traits::fieldList<PointTDiff>::type FieldListOutT; 00181 typedef typename pcl::intersect<FieldListInT, FieldListOutT>::type FieldList; 00182 pcl::for_each_type <FieldList> (pcl::NdConcatenateFunctor <PointTDiff, PointT> (point, p)); 00183 return (nearestKSearch (p, k, k_indices, k_sqr_distances)); 00184 } 00185 00203 virtual int 00204 nearestKSearch (int index, int k, 00205 std::vector<int> &k_indices, std::vector<float> &k_sqr_distances) const 00206 { 00207 if (indices_ == NULL) 00208 { 00209 assert (index >= 0 && index < static_cast<int> (input_->points.size ()) && "Out-of-bounds error in nearestKSearch!"); 00210 return (nearestKSearch (input_->points[index], k, k_indices, k_sqr_distances)); 00211 } 00212 else 00213 { 00214 assert (index >= 0 && index < static_cast<int> (indices_->size ()) && "Out-of-bounds error in nearestKSearch!"); 00215 return (nearestKSearch (input_->points[(*indices_)[index]], k, k_indices, k_sqr_distances)); 00216 } 00217 } 00218 00229 virtual int 00230 radiusSearch (const PointT &p_q, double radius, std::vector<int> &k_indices, 00231 std::vector<float> &k_sqr_distances, unsigned int max_nn = 0) const = 0; 00232 00250 virtual int 00251 radiusSearch (const PointCloud &cloud, int index, double radius, 00252 std::vector<int> &k_indices, std::vector<float> &k_sqr_distances, 00253 unsigned int max_nn = 0) const 00254 { 00255 assert (index >= 0 && index < static_cast<int> (cloud.points.size ()) && "Out-of-bounds error in radiusSearch!"); 00256 return (radiusSearch(cloud.points[index], radius, k_indices, k_sqr_distances, max_nn)); 00257 } 00258 00269 template <typename PointTDiff> inline int 00270 radiusSearchT (const PointTDiff &point, double radius, std::vector<int> &k_indices, 00271 std::vector<float> &k_sqr_distances, unsigned int max_nn = 0) const 00272 { 00273 PointT p; 00274 // Copy all the data fields from the input cloud to the output one 00275 typedef typename pcl::traits::fieldList<PointT>::type FieldListInT; 00276 typedef typename pcl::traits::fieldList<PointTDiff>::type FieldListOutT; 00277 typedef typename pcl::intersect<FieldListInT, FieldListOutT>::type FieldList; 00278 pcl::for_each_type <FieldList> (pcl::NdConcatenateFunctor <PointTDiff, PointT> (point, p)); 00279 return (radiusSearch (p, radius, k_indices, k_sqr_distances, max_nn)); 00280 } 00281 00301 virtual int 00302 radiusSearch (int index, double radius, std::vector<int> &k_indices, 00303 std::vector<float> &k_sqr_distances, unsigned int max_nn = 0) const 00304 { 00305 if (indices_ == NULL) 00306 { 00307 assert (index >= 0 && index < static_cast<int> (input_->points.size ()) && "Out-of-bounds error in radiusSearch!"); 00308 return (radiusSearch (input_->points[index], radius, k_indices, k_sqr_distances, max_nn)); 00309 } 00310 else 00311 { 00312 assert (index >= 0 && index < static_cast<int> (indices_->size ()) && "Out-of-bounds error in radiusSearch!"); 00313 return (radiusSearch (input_->points[(*indices_)[index]], radius, k_indices, k_sqr_distances, max_nn)); 00314 } 00315 } 00316 00320 virtual inline void 00321 setEpsilon (float eps) 00322 { 00323 epsilon_ = eps; 00324 } 00325 00327 inline float 00328 getEpsilon () const 00329 { 00330 return (epsilon_); 00331 } 00332 00336 inline void 00337 setMinPts (int min_pts) 00338 { 00339 min_pts_ = min_pts; 00340 } 00341 00343 inline int 00344 getMinPts () const 00345 { 00346 return (min_pts_); 00347 } 00348 00349 protected: 00351 PointCloudConstPtr input_; 00352 00354 IndicesConstPtr indices_; 00355 00357 float epsilon_; 00358 00360 int min_pts_; 00361 00363 bool sorted_; 00364 00366 PointRepresentationConstPtr point_representation_; 00367 00369 virtual std::string 00370 getName () const = 0; 00371 }; 00372 } 00373 00374 #endif //#ifndef _PCL_KDTREE_KDTREE_H_
1.7.6.1