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) 2010-2011, Willow Garage, Inc. 00006 * Copyright (c) 2012-, Open Perception, Inc. 00007 * 00008 * All rights reserved. 00009 * 00010 * Redistribution and use in source and binary forms, with or without 00011 * modification, are permitted provided that the following conditions 00012 * are met: 00013 * 00014 * * Redistributions of source code must retain the above copyright 00015 * notice, this list of conditions and the following disclaimer. 00016 * * Redistributions in binary form must reproduce the above 00017 * copyright notice, this list of conditions and the following 00018 * disclaimer in the documentation and/or other materials provided 00019 * with the distribution. 00020 * * Neither the name of the copyright holder(s) nor the names of its 00021 * contributors may be used to endorse or promote products derived 00022 * from this software without specific prior written permission. 00023 * 00024 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00025 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00026 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00027 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00028 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00029 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00030 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00031 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00032 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00033 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00034 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00035 * POSSIBILITY OF SUCH DAMAGE. 00036 * 00037 * $Id$ 00038 * 00039 */ 00040 #ifndef PCL_INTENSITY_SPIN_H_ 00041 #define PCL_INTENSITY_SPIN_H_ 00042 00043 #include <pcl/features/feature.h> 00044 00045 namespace pcl 00046 { 00047 /** \brief IntensitySpinEstimation estimates the intensity-domain spin image descriptors for a given point cloud 00048 * dataset containing points and intensity. For more information about the intensity-domain spin image descriptor, 00049 * see: 00050 * 00051 * Svetlana Lazebnik, Cordelia Schmid, and Jean Ponce. 00052 * A sparse texture representation using local affine regions. 00053 * In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 27, pages 1265-1278, August 2005. 00054 * \author Michael Dixon 00055 * \ingroup features 00056 */ 00057 template <typename PointInT, typename PointOutT> 00058 class IntensitySpinEstimation: public Feature<PointInT, PointOutT> 00059 { 00060 public: 00061 typedef boost::shared_ptr<IntensitySpinEstimation<PointInT, PointOutT> > Ptr; 00062 typedef boost::shared_ptr<const IntensitySpinEstimation<PointInT, PointOutT> > ConstPtr; 00063 using Feature<PointInT, PointOutT>::feature_name_; 00064 using Feature<PointInT, PointOutT>::getClassName; 00065 00066 using Feature<PointInT, PointOutT>::input_; 00067 using Feature<PointInT, PointOutT>::indices_; 00068 using Feature<PointInT, PointOutT>::surface_; 00069 00070 using Feature<PointInT, PointOutT>::tree_; 00071 using Feature<PointInT, PointOutT>::search_radius_; 00072 00073 typedef typename pcl::PointCloud<PointInT> PointCloudIn; 00074 typedef typename Feature<PointInT, PointOutT>::PointCloudOut PointCloudOut; 00075 00076 /** \brief Empty constructor. */ 00077 IntensitySpinEstimation () : nr_distance_bins_ (4), nr_intensity_bins_ (5), sigma_ (1.0) 00078 { 00079 feature_name_ = "IntensitySpinEstimation"; 00080 }; 00081 00082 /** \brief Estimate the intensity-domain spin image descriptor for a given point based on its spatial 00083 * neighborhood of 3D points and their intensities. 00084 * \param[in] cloud the dataset containing the Cartesian coordinates and intensity values of the points 00085 * \param[in] radius the radius of the feature 00086 * \param[in] sigma the standard deviation of the Gaussian smoothing kernel to use during the soft histogram update 00087 * \param[in] k the number of neighbors to use from \a indices and \a squared_distances 00088 * \param[in] indices the indices of the points that comprise the query point's neighborhood 00089 * \param[in] squared_distances the squared distances from the query point to each point in the neighborhood 00090 * \param[out] intensity_spin_image the resultant intensity-domain spin image descriptor 00091 */ 00092 void 00093 computeIntensitySpinImage (const PointCloudIn &cloud, 00094 float radius, float sigma, int k, 00095 const std::vector<int> &indices, 00096 const std::vector<float> &squared_distances, 00097 Eigen::MatrixXf &intensity_spin_image); 00098 00099 /** \brief Set the number of bins to use in the distance dimension of the spin image 00100 * \param[in] nr_distance_bins the number of bins to use in the distance dimension of the spin image 00101 */ 00102 inline void 00103 setNrDistanceBins (size_t nr_distance_bins) { nr_distance_bins_ = static_cast<int> (nr_distance_bins); }; 00104 00105 /** \brief Returns the number of bins in the distance dimension of the spin image. */ 00106 inline int 00107 getNrDistanceBins () { return (nr_distance_bins_); }; 00108 00109 /** \brief Set the number of bins to use in the intensity dimension of the spin image. 00110 * \param[in] nr_intensity_bins the number of bins to use in the intensity dimension of the spin image 00111 */ 00112 inline void 00113 setNrIntensityBins (size_t nr_intensity_bins) { nr_intensity_bins_ = static_cast<int> (nr_intensity_bins); }; 00114 00115 /** \brief Returns the number of bins in the intensity dimension of the spin image. */ 00116 inline int 00117 getNrIntensityBins () { return (nr_intensity_bins_); }; 00118 00119 /** \brief Set the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images. 00120 * \param[in] sigma the standard deviation of the Gaussian smoothing kernel to use when constructing the spin images 00121 */ 00122 inline void 00123 setSmoothingBandwith (float sigma) { sigma_ = sigma; }; 00124 00125 /** \brief Returns the standard deviation of the Gaussian smoothing kernel used to construct the spin images. */ 00126 inline float 00127 getSmoothingBandwith () { return (sigma_); }; 00128 00129 00130 /** \brief Estimate the intensity-domain descriptors at a set of points given by <setInputCloud (), setIndices ()> 00131 * using the surface in setSearchSurface (), and the spatial locator in setSearchMethod (). 00132 * \param[out] output the resultant point cloud model dataset that contains the intensity-domain spin image features 00133 */ 00134 void 00135 computeFeature (PointCloudOut &output); 00136 00137 /** \brief The number of distance bins in the descriptor. */ 00138 int nr_distance_bins_; 00139 00140 /** \brief The number of intensity bins in the descriptor. */ 00141 int nr_intensity_bins_; 00142 00143 /** \brief The standard deviation of the Gaussian smoothing kernel used to construct the spin images. */ 00144 float sigma_; 00145 }; 00146 } 00147 00148 #ifdef PCL_NO_PRECOMPILE 00149 #include <pcl/features/impl/intensity_spin.hpp> 00150 #endif 00151 00152 #endif // #ifndef PCL_INTENSITY_SPIN_H_