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) 2009-2012, 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: sac_model_normal_sphere.h schrandt $ 00038 * 00039 */ 00040 00041 #ifndef PCL_SAMPLE_CONSENSUS_MODEL_NORMALSPHERE_H_ 00042 #define PCL_SAMPLE_CONSENSUS_MODEL_NORMALSPHERE_H_ 00043 00044 #include <pcl/sample_consensus/sac_model.h> 00045 #include <pcl/sample_consensus/sac_model_sphere.h> 00046 #include <pcl/sample_consensus/model_types.h> 00047 #include <pcl/common/common.h> 00048 00049 namespace pcl 00050 { 00051 /** \brief @b SampleConsensusModelNormalSphere defines a model for 3D sphere 00052 * segmentation using additional surface normal constraints. Basically this 00053 * means that checking for inliers will not only involve a "distance to 00054 * model" criterion, but also an additional "maximum angular deviation" 00055 * between the sphere's normal and the inlier points normals. 00056 * 00057 * The model coefficients are defined as: 00058 * <ul> 00059 * <li><b>a</b> : the X coordinate of the plane's normal (normalized) 00060 * <li><b>b</b> : the Y coordinate of the plane's normal (normalized) 00061 * <li><b>c</b> : the Z coordinate of the plane's normal (normalized) 00062 * <li><b>d</b> : radius of the sphere 00063 * </ul> 00064 * 00065 * \author Stefan Schrandt 00066 * \ingroup sample_consensus 00067 */ 00068 template <typename PointT, typename PointNT> 00069 class SampleConsensusModelNormalSphere : public SampleConsensusModelSphere<PointT>, public SampleConsensusModelFromNormals<PointT, PointNT> 00070 { 00071 public: 00072 using SampleConsensusModel<PointT>::input_; 00073 using SampleConsensusModel<PointT>::indices_; 00074 using SampleConsensusModel<PointT>::radius_min_; 00075 using SampleConsensusModel<PointT>::radius_max_; 00076 using SampleConsensusModelFromNormals<PointT, PointNT>::normals_; 00077 using SampleConsensusModelFromNormals<PointT, PointNT>::normal_distance_weight_; 00078 using SampleConsensusModel<PointT>::error_sqr_dists_; 00079 00080 typedef typename SampleConsensusModel<PointT>::PointCloud PointCloud; 00081 typedef typename SampleConsensusModel<PointT>::PointCloudPtr PointCloudPtr; 00082 typedef typename SampleConsensusModel<PointT>::PointCloudConstPtr PointCloudConstPtr; 00083 00084 typedef typename SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNPtr PointCloudNPtr; 00085 typedef typename SampleConsensusModelFromNormals<PointT, PointNT>::PointCloudNConstPtr PointCloudNConstPtr; 00086 00087 typedef boost::shared_ptr<SampleConsensusModelNormalSphere> Ptr; 00088 00089 /** \brief Constructor for base SampleConsensusModelNormalSphere. 00090 * \param[in] cloud the input point cloud dataset 00091 * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false) 00092 */ 00093 SampleConsensusModelNormalSphere (const PointCloudConstPtr &cloud, 00094 bool random = false) 00095 : SampleConsensusModelSphere<PointT> (cloud, random) 00096 , SampleConsensusModelFromNormals<PointT, PointNT> () 00097 { 00098 } 00099 00100 /** \brief Constructor for base SampleConsensusModelNormalSphere. 00101 * \param[in] cloud the input point cloud dataset 00102 * \param[in] indices a vector of point indices to be used from \a cloud 00103 * \param[in] random if true set the random seed to the current time, else set to 12345 (default: false) 00104 */ 00105 SampleConsensusModelNormalSphere (const PointCloudConstPtr &cloud, 00106 const std::vector<int> &indices, 00107 bool random = false) 00108 : SampleConsensusModelSphere<PointT> (cloud, indices, random) 00109 , SampleConsensusModelFromNormals<PointT, PointNT> () 00110 { 00111 } 00112 00113 /** \brief Empty destructor */ 00114 virtual ~SampleConsensusModelNormalSphere () {} 00115 00116 /** \brief Select all the points which respect the given model coefficients as inliers. 00117 * \param[in] model_coefficients the coefficients of a sphere model that we need to compute distances to 00118 * \param[in] threshold a maximum admissible distance threshold for determining the inliers from the outliers 00119 * \param[out] inliers the resultant model inliers 00120 */ 00121 void 00122 selectWithinDistance (const Eigen::VectorXf &model_coefficients, 00123 const double threshold, 00124 std::vector<int> &inliers); 00125 00126 /** \brief Count all the points which respect the given model coefficients as inliers. 00127 * \param[in] model_coefficients the coefficients of a model that we need to compute distances to 00128 * \param[in] threshold maximum admissible distance threshold for determining the inliers from the outliers 00129 * \return the resultant number of inliers 00130 */ 00131 virtual int 00132 countWithinDistance (const Eigen::VectorXf &model_coefficients, 00133 const double threshold); 00134 00135 /** \brief Compute all distances from the cloud data to a given sphere model. 00136 * \param[in] model_coefficients the coefficients of a sphere model that we need to compute distances to 00137 * \param[out] distances the resultant estimated distances 00138 */ 00139 void 00140 getDistancesToModel (const Eigen::VectorXf &model_coefficients, 00141 std::vector<double> &distances); 00142 00143 /** \brief Return an unique id for this model (SACMODEL_NORMAL_SPHERE). */ 00144 inline pcl::SacModel 00145 getModelType () const { return (SACMODEL_NORMAL_SPHERE); } 00146 00147 EIGEN_MAKE_ALIGNED_OPERATOR_NEW 00148 00149 protected: 00150 /** \brief Check whether a model is valid given the user constraints. 00151 * \param[in] model_coefficients the set of model coefficients 00152 */ 00153 bool 00154 isModelValid (const Eigen::VectorXf &model_coefficients); 00155 00156 }; 00157 } 00158 00159 #ifdef PCL_NO_PRECOMPILE 00160 #include <pcl/sample_consensus/impl/sac_model_normal_sphere.hpp> 00161 #endif 00162 00163 #endif //#ifndef PCL_SAMPLE_CONSENSUS_MODEL_NORMALSPHERE_H_