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 */ 00037 00038 #ifndef PCL_KEYPOINT_IMPL_H_ 00039 #define PCL_KEYPOINT_IMPL_H_ 00040 00042 template <typename PointInT, typename PointOutT> bool 00043 pcl::Keypoint<PointInT, PointOutT>::initCompute () 00044 { 00045 if (!PCLBase<PointInT>::initCompute ()) 00046 return (false); 00047 00048 // Initialize the spatial locator 00049 if (!tree_) 00050 { 00051 if (input_->isOrganized ()) 00052 tree_.reset (new pcl::search::OrganizedNeighbor<PointInT> ()); 00053 else 00054 tree_.reset (new pcl::search::KdTree<PointInT> (false)); 00055 } 00056 return (true); 00057 } 00058 00060 template <typename PointInT, typename PointOutT> inline void 00061 pcl::Keypoint<PointInT, PointOutT>::compute (PointCloudOut &output) 00062 { 00063 if (!initCompute ()) 00064 { 00065 PCL_ERROR ("[pcl::%s::compute] initCompute failed!\n", getClassName ().c_str ()); 00066 return; 00067 } 00068 00069 // If no search surface has been defined, use the input dataset as the search surface itself 00070 if (!surface_) 00071 surface_ = input_; 00072 00073 // Send the surface dataset to the spatial locator 00074 tree_->setInputCloud (surface_); 00075 00076 // Do a fast check to see if the search parameters are well defined 00077 if (search_radius_ != 0.0) 00078 { 00079 if (k_ != 0) 00080 { 00081 PCL_ERROR ("[pcl::%s::compute] Both radius (%f) and K (%d) defined! Set one of them to zero first and then re-run compute ().\n", getClassName ().c_str (), search_radius_, k_); 00082 return; 00083 } 00084 else // Use the radiusSearch () function 00085 { 00086 search_parameter_ = search_radius_; 00087 if (surface_ == input_) // if the two surfaces are the same 00088 { 00089 // Declare the search locator definition 00090 int (KdTree::*radiusSearch)(int index, double radius, std::vector<int> &k_indices, 00091 std::vector<float> &k_distances, int max_nn) const = &KdTree::radiusSearch; 00092 search_method_ = boost::bind (radiusSearch, boost::ref (tree_), _1, _2, _3, _4, INT_MAX); 00093 } 00094 else 00095 { 00096 // Declare the search locator definition 00097 int (KdTree::*radiusSearchSurface)(const PointCloudIn &cloud, int index, double radius, std::vector<int> &k_indices, 00098 std::vector<float> &k_distances, int max_nn) = &KdTree::radiusSearch; 00099 search_method_surface_ = boost::bind (radiusSearchSurface, boost::ref (tree_), _1, _2, _3, _4, _5, INT_MAX); 00100 } 00101 } 00102 } 00103 else 00104 { 00105 if (k_ != 0) // Use the nearestKSearch () function 00106 { 00107 search_parameter_ = k_; 00108 if (surface_ == input_) // if the two surfaces are the same 00109 { 00110 // Declare the search locator definition 00111 int (KdTree::*nearestKSearch)(int index, int k, std::vector<int> &k_indices, std::vector<float> &k_distances) = &KdTree::nearestKSearch; 00112 search_method_ = boost::bind (nearestKSearch, boost::ref (tree_), _1, _2, _3, _4); 00113 } 00114 else 00115 { 00116 // Declare the search locator definition 00117 int (KdTree::*nearestKSearchSurface)(const PointCloudIn &cloud, int index, int k, std::vector<int> &k_indices, std::vector<float> &k_distances) = &KdTree::nearestKSearch; 00118 search_method_surface_ = boost::bind (nearestKSearchSurface, boost::ref (tree_), _1, _2, _3, _4, _5); 00119 } 00120 } 00121 else 00122 { 00123 PCL_ERROR ("[pcl::%s::compute] Neither radius nor K defined! Set one of them to a positive number first and then re-run compute ().\n", getClassName ().c_str ()); 00124 return; 00125 } 00126 } 00127 00128 // Perform the actual computation 00129 detectKeypoints (output); 00130 00131 deinitCompute (); 00132 00133 // Reset the surface 00134 if (input_ == surface_) 00135 surface_.reset (); 00136 } 00137 00138 #endif //#ifndef PCL_KEYPOINT_IMPL_H_ 00139