io.hpp
Go to the documentation of this file.
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 


pcl
Author(s): Open Perception
autogenerated on Mon Oct 6 2014 03:15:31