Point Cloud Library (PCL)
1.7.0
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00001 /* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Point Cloud Library (PCL) - www.pointclouds.org 00005 * Copyright (c) 2012-, Open Perception. 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 the copyright holder(s) 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 * $Id$ 00037 * 00038 */ 00039 00040 #ifndef PCL_FILTERS_PYRAMID_H_ 00041 #define PCL_FILTERS_PYRAMID_H_ 00042 00043 #include <pcl/common/point_operators.h> 00044 #include <pcl/point_cloud.h> 00045 #include <pcl/pcl_config.h> 00046 00047 namespace pcl 00048 { 00049 namespace filters 00050 { 00051 /** Pyramid constructs a multi-scale representation of an organised point cloud. 00052 * It is an iterative smoothing subsampling algorithm. 00053 * The subsampling is fixed to 2. Two smoothing kernels may be used: 00054 * - [1/16 1/4 3/8 1/4 1/16] slower but produces finer result; 00055 * - [1/4 1/2 1/2] the more conventional binomial kernel which is faster. 00056 * We use a memory efficient algorithm so the convolving and subsampling are combined in a 00057 * single step. 00058 * 00059 * \author Nizar Sallem 00060 */ 00061 template <typename PointT> 00062 class Pyramid 00063 { 00064 public: 00065 typedef typename PointCloud<PointT>::Ptr PointCloudPtr; 00066 typedef typename PointCloud<PointT>::ConstPtr PointCloudConstPtr; 00067 typedef boost::shared_ptr< Pyramid<PointT> > Ptr; 00068 typedef boost::shared_ptr< const Pyramid<PointT> > ConstPtr; 00069 00070 Pyramid (int levels = 4) 00071 : levels_ (levels) 00072 , large_ (false) 00073 , threshold_ (0.01) 00074 , threads_ (0) 00075 { 00076 name_ = "Pyramid"; 00077 } 00078 00079 /** \brief Provide a pointer to the input dataset 00080 * \param cloud the const boost shared pointer to a PointCloud message 00081 */ 00082 inline void 00083 setInputCloud (const PointCloudConstPtr &cloud) { input_ = cloud; } 00084 00085 /** \brief Get a pointer to the input point cloud dataset. */ 00086 inline PointCloudConstPtr const 00087 getInputCloud () { return (input_); } 00088 00089 /** \brief Set the number of pyramid levels 00090 * \param levels desired number of pyramid levels 00091 */ 00092 inline void 00093 setNumberOfLevels (int levels) { levels_ = levels; } 00094 00095 /// \brief \return the number of pyramid levels 00096 inline int 00097 getNumberOfLevels () const { return (levels_); } 00098 00099 /** \brief Initialize the scheduler and set the number of threads to use. 00100 * \param nr_threads the number of hardware threads to use (0 sets the value back to automatic). 00101 */ 00102 inline void 00103 setNumberOfThreads (unsigned int nr_threads = 0) { threads_ = nr_threads; } 00104 00105 /** \brief Choose a larger smoothing kernel for enhanced smoothing. 00106 * \param large if true large smoothng kernel will be used. 00107 */ 00108 inline void 00109 setLargeSmoothingKernel (bool large) { large_ = large; } 00110 00111 /** Only points such us distance (center,point) < threshold are accounted for to prevent 00112 * ghost points. 00113 * Default value is 0.01, to disable set to std::numeric<float>::infinity (). 00114 * \param[in] threshold maximum allowed distance between center and neighbor. 00115 */ 00116 inline void 00117 setDistanceThreshold (float threshold) { threshold_ = threshold; } 00118 00119 /// \return the distance threshold 00120 inline float 00121 getDistanceThreshold () const { return (threshold_); } 00122 00123 /** \brief compute the pyramid levels. 00124 * \param[out] output the constructed pyramid. It is resized to the number of levels. 00125 * \remark input_ is copied to output[0] for consistency reasons. 00126 */ 00127 void 00128 compute (std::vector<PointCloudPtr>& output); 00129 00130 inline const std::string& 00131 getClassName () const { return (name_); } 00132 00133 private: 00134 00135 /// \brief init computation 00136 bool 00137 initCompute (); 00138 00139 /** \brief nullify a point 00140 * \param[in][out] p point to nullify 00141 */ 00142 inline void 00143 nullify (PointT& p) const 00144 { 00145 p.x = p.y = p.z = std::numeric_limits<float>::quiet_NaN (); 00146 } 00147 00148 /// \brief The input point cloud dataset. 00149 PointCloudConstPtr input_; 00150 /// \brief number of pyramid levels 00151 int levels_; 00152 /// \brief use large smoothing kernel 00153 bool large_; 00154 /// \brief filter name 00155 std::string name_; 00156 /// \brief smoothing kernel 00157 Eigen::MatrixXf kernel_; 00158 /// Threshold distance between adjacent points 00159 float threshold_; 00160 /// \brief number of threads 00161 unsigned int threads_; 00162 00163 public: 00164 EIGEN_MAKE_ALIGNED_OPERATOR_NEW 00165 }; 00166 } 00167 } 00168 00169 #endif