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_INTEGRALIMAGE_BASED_NORMAL_ESTIMATOR_H_ 00039 #define PCL_INTEGRALIMAGE_BASED_NORMAL_ESTIMATOR_H_ 00040 00041 #include <pcl/point_cloud.h> 00042 #include <pcl/point_types.h> 00043 #include "pcl/features/feature.h" 00044 #include "pcl/features/integral_image_2d.h" 00045 #include "pcl/features/integral_image2D.h" 00046 00047 namespace pcl 00048 { 00053 template <typename PointInT, typename PointOutT> 00054 class IntegralImageNormalEstimation: public Feature<PointInT, PointOutT> 00055 { 00056 using Feature<PointInT, PointOutT>::input_; 00057 using Feature<PointInT, PointOutT>::feature_name_; 00058 using Feature<PointInT, PointOutT>::tree_; 00059 using Feature<PointInT, PointOutT>::k_; 00060 00061 public: 00062 00063 enum NormalEstimationMethod 00064 { 00065 COVARIANCE_MATRIX, 00066 AVERAGE_3D_GRADIENT, 00067 AVERAGE_DEPTH_CHANGE 00068 }; 00069 00070 typedef typename Feature<PointInT, PointOutT>::PointCloudIn PointCloudIn; 00071 typedef typename Feature<PointInT, PointOutT>::PointCloudOut PointCloudOut; 00072 00074 IntegralImageNormalEstimation () : 00075 normal_estimation_method_(AVERAGE_3D_GRADIENT), 00076 integral_image_x_(NULL), integral_image_y_(NULL), 00077 integral_image_xyz_(NULL), integral_image_(NULL), 00078 integral_image_XYZ_ (true), 00079 diff_x_(NULL), diff_y_(NULL), depth_data_(NULL), 00080 use_depth_dependent_smoothing_(false), 00081 max_depth_change_factor_(20.0f*0.001f), 00082 normal_smoothing_size_(10.0f), 00083 init_covariance_matrix_(false), init_average_3d_gradient_(false), init_depth_change_(false) 00084 { 00085 feature_name_ = "IntegralImagesNormalEstimation"; 00086 tree_.reset (); 00087 k_ = 1; 00088 } 00089 00090 00092 virtual ~IntegralImageNormalEstimation (); 00093 00098 void 00099 setRectSize (const int width, const int height); 00100 00106 void 00107 computePointNormal (const int pos_x, const int pos_y, PointOutT &normal); 00108 00113 void 00114 setMaxDepthChangeFactor (float max_depth_change_factor) 00115 { 00116 max_depth_change_factor_ = max_depth_change_factor; 00117 } 00118 00123 void 00124 setNormalSmoothingSize (float normal_smoothing_size) 00125 { 00126 normal_smoothing_size_ = normal_smoothing_size; 00127 } 00128 00141 void 00142 setNormalEstimationMethod (NormalEstimationMethod normal_estimation_method) 00143 { 00144 normal_estimation_method_ = normal_estimation_method; 00145 } 00146 00150 void 00151 setDepthDependentSmoothing (bool use_depth_dependent_smoothing) 00152 { 00153 use_depth_dependent_smoothing_ = use_depth_dependent_smoothing; 00154 } 00155 00159 virtual inline void 00160 setInputCloud (const typename PointCloudIn::ConstPtr &cloud) 00161 { 00162 input_ = cloud; 00163 00164 init_covariance_matrix_ = init_average_3d_gradient_ = init_depth_change_ = false; 00165 00166 // Initialize the correct data structure based on the normal estimation method chosen 00167 initData (); 00168 } 00169 00170 protected: 00171 00175 void 00176 computeFeature (PointCloudOut &output); 00177 00180 void 00181 initData (); 00182 00183 private: 00190 NormalEstimationMethod normal_estimation_method_; 00191 00193 int rect_width_; 00195 int rect_height_; 00196 00198 float distance_threshold_; 00199 00201 IntegralImage2D<float, double> *integral_image_x_; 00203 IntegralImage2D<float, double> *integral_image_y_; 00205 IntegralImage2D<float, double> *integral_image_xyz_; 00207 IntegralImage2D<float, double> *integral_image_; 00209 IntegralImage2Dim<float, 3> integral_image_XYZ_; 00210 00212 float *diff_x_; 00214 float *diff_y_; 00215 00217 float *depth_data_; 00218 00220 bool use_depth_dependent_smoothing_; 00221 00223 float max_depth_change_factor_; 00224 00226 float normal_smoothing_size_; 00227 00229 bool init_covariance_matrix_; 00230 00232 bool init_average_3d_gradient_; 00233 00235 bool init_depth_change_; 00236 00238 void 00239 initCovarianceMatrixMethod (); 00240 00242 void 00243 initAverage3DGradientMethod (); 00244 00246 void 00247 initAverageDepthChangeMethod (); 00248 }; 00249 } 00250 00251 #endif 00252