Point Cloud Library (PCL)
1.3.1
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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 * $Id: io.hpp 3021 2011-11-01 03:41:25Z svn $ 00037 * 00038 */ 00039 00040 #ifndef PCL_KDTREE_IO_IMPL_HPP_ 00041 #define PCL_KDTREE_IO_IMPL_HPP_ 00042 00043 #include <pcl/kdtree/io.h> 00044 #include <pcl/kdtree/kdtree_flann.h> 00045 00047 template <typename Point1T, typename Point2T> void 00048 pcl::getApproximateIndices ( 00049 const typename pcl::PointCloud<Point1T>::Ptr &cloud_in, 00050 const typename pcl::PointCloud<Point2T>::Ptr &cloud_ref, 00051 std::vector<int> &indices) 00052 { 00053 pcl::KdTreeFLANN<Point2T> tree; 00054 tree.setInputCloud (cloud_ref); 00055 00056 std::vector<int> nn_idx (1); 00057 std::vector<float> nn_dists (1); 00058 indices.resize (cloud_in->points.size ()); 00059 for (size_t i = 0; i < cloud_in->points.size (); ++i) 00060 { 00061 tree.nearestKSearch (*cloud_in, i, 1, nn_idx, nn_dists); 00062 indices[i] = nn_idx[0]; 00063 } 00064 } 00065 00067 template <typename PointT> void 00068 pcl::getApproximateIndices ( 00069 const typename pcl::PointCloud<PointT>::Ptr &cloud_in, 00070 const typename pcl::PointCloud<PointT>::Ptr &cloud_ref, 00071 std::vector<int> &indices) 00072 { 00073 pcl::KdTreeFLANN<PointT> tree; 00074 tree.setInputCloud (cloud_ref); 00075 00076 std::vector<int> nn_idx (1); 00077 std::vector<float> nn_dists (1); 00078 indices.resize (cloud_in->points.size ()); 00079 for (size_t i = 0; i < cloud_in->points.size (); ++i) 00080 { 00081 tree.nearestKSearch (*cloud_in, i, 1, nn_idx, nn_dists); 00082 indices[i] = nn_idx[0]; 00083 } 00084 } 00085 00086 #endif // PCL_KDTREE_IO_IMPL_H_ 00087