Point Cloud Library (PCL)
1.3.1
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00001 /* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Copyright (c) 2010, 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: distances.h 2386 2011-09-02 21:28:26Z rusu $ 00035 * 00036 */ 00037 #ifndef PCL_DISTANCES_H_ 00038 #define PCL_DISTANCES_H_ 00039 00040 #include <pcl/common/common.h> 00041 00049 namespace pcl 00050 { 00058 PCL_EXPORTS void 00059 lineToLineSegment (const Eigen::VectorXf &line_a, const Eigen::VectorXf &line_b, 00060 Eigen::Vector4f &pt1_seg, Eigen::Vector4f &pt2_seg); 00061 00068 double inline 00069 sqrPointToLineDistance (const Eigen::Vector4f &pt, const Eigen::Vector4f &line_pt, const Eigen::Vector4f &line_dir) 00070 { 00071 // Calculate the distance from the point to the line 00072 // D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p1-p0)) / norm(p2-p1) 00073 return (line_dir.cross3 (line_pt - pt)).squaredNorm () / line_dir.squaredNorm (); 00074 } 00075 00084 double inline 00085 sqrPointToLineDistance (const Eigen::Vector4f &pt, const Eigen::Vector4f &line_pt, const Eigen::Vector4f &line_dir, const double sqr_length) 00086 { 00087 // Calculate the distance from the point to the line 00088 // D = ||(P2-P1) x (P1-P0)|| / ||P2-P1|| = norm (cross (p2-p1, p1-p0)) / norm(p2-p1) 00089 return (line_dir.cross3 (line_pt - pt)).squaredNorm () / sqr_length; 00090 } 00091 00099 template <typename PointT> double inline 00100 getMaxSegment (const pcl::PointCloud<PointT> &cloud, 00101 PointT &pmin, PointT &pmax) 00102 { 00103 double max_dist = std::numeric_limits<double>::min (); 00104 int i_min = -1, i_max = -1; 00105 00106 for (size_t i = 0; i < cloud.points.size (); ++i) 00107 { 00108 for (size_t j = i; j < cloud.points.size (); ++j) 00109 { 00110 // Compute the distance 00111 double dist = (cloud.points[i].getVector4fMap () - 00112 cloud.points[j].getVector4fMap ()).squaredNorm (); 00113 if (dist <= max_dist) 00114 continue; 00115 00116 max_dist = dist; 00117 i_min = i; 00118 i_max = j; 00119 } 00120 } 00121 00122 if (i_min == -1 || i_max == -1) 00123 return (max_dist = std::numeric_limits<double>::min ()); 00124 00125 pmin = cloud.points[i_min]; 00126 pmax = cloud.points[i_max]; 00127 return (std::sqrt (max_dist)); 00128 } 00129 00138 template <typename PointT> double inline 00139 getMaxSegment (const pcl::PointCloud<PointT> &cloud, const std::vector<int> &indices, 00140 PointT &pmin, PointT &pmax) 00141 { 00142 double max_dist = std::numeric_limits<double>::min (); 00143 int i_min = -1, i_max = -1; 00144 00145 for (size_t i = 0; i < indices.size (); ++i) 00146 { 00147 for (size_t j = i; j < indices.size (); ++j) 00148 { 00149 // Compute the distance 00150 double dist = (cloud.points[indices[i]].getVector4fMap () - 00151 cloud.points[indices[j]].getVector4fMap ()).squaredNorm (); 00152 if (dist <= max_dist) 00153 continue; 00154 00155 max_dist = dist; 00156 i_min = i; 00157 i_max = j; 00158 } 00159 } 00160 00161 if (i_min == -1 || i_max == -1) 00162 return (max_dist = std::numeric_limits<double>::min ()); 00163 00164 pmin = cloud.points[indices[i_min]]; 00165 pmax = cloud.points[indices[i_max]]; 00166 return (std::sqrt (max_dist)); 00167 } 00168 } 00169 /*@*/ 00170 #endif //#ifndef PCL_DISTANCES_H_ 00171