Point Cloud Library (PCL)  1.5.1
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines
sac_model_sphere.h
Go to the documentation of this file.
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  * $Id: sac_model_sphere.h 4702 2012-02-23 09:39:33Z gedikli $
00037  *
00038  */
00039 
00040 #ifndef PCL_SAMPLE_CONSENSUS_MODEL_SPHERE_H_
00041 #define PCL_SAMPLE_CONSENSUS_MODEL_SPHERE_H_
00042 
00043 #include <pcl/sample_consensus/sac_model.h>
00044 #include <pcl/sample_consensus/model_types.h>
00045 
00046 namespace pcl
00047 {
00058   template <typename PointT>
00059   class SampleConsensusModelSphere : public SampleConsensusModel<PointT>
00060   {
00061     using SampleConsensusModel<PointT>::input_;
00062     using SampleConsensusModel<PointT>::indices_;
00063     using SampleConsensusModel<PointT>::radius_min_;
00064     using SampleConsensusModel<PointT>::radius_max_;
00065 
00066     public:
00067       typedef typename SampleConsensusModel<PointT>::PointCloud PointCloud;
00068       typedef typename SampleConsensusModel<PointT>::PointCloudPtr PointCloudPtr;
00069       typedef typename SampleConsensusModel<PointT>::PointCloudConstPtr PointCloudConstPtr;
00070 
00071       typedef boost::shared_ptr<SampleConsensusModelSphere> Ptr;
00072 
00076       SampleConsensusModelSphere (const PointCloudConstPtr &cloud) : SampleConsensusModel<PointT> (cloud) { }
00077 
00082       SampleConsensusModelSphere (const PointCloudConstPtr &cloud, const std::vector<int> &indices) : SampleConsensusModel<PointT> (cloud, indices) { }
00083 
00094       void 
00095       getSamples (int &iterations, std::vector<int> &samples);
00096 
00103       bool 
00104       computeModelCoefficients (const std::vector<int> &samples, 
00105                                 Eigen::VectorXf &model_coefficients);
00106 
00111       void 
00112       getDistancesToModel (const Eigen::VectorXf &model_coefficients, 
00113                            std::vector<double> &distances);
00114 
00120       void 
00121       selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
00122                             const double threshold, 
00123                             std::vector<int> &inliers);
00124 
00131       virtual int
00132       countWithinDistance (const Eigen::VectorXf &model_coefficients, 
00133                            const double threshold);
00134 
00141       void 
00142       optimizeModelCoefficients (const std::vector<int> &inliers, 
00143                                  const Eigen::VectorXf &model_coefficients, 
00144                                  Eigen::VectorXf &optimized_coefficients);
00145 
00153       void 
00154       projectPoints (const std::vector<int> &inliers, 
00155                      const Eigen::VectorXf &model_coefficients, 
00156                      PointCloud &projected_points, 
00157                      bool copy_data_fields = true);
00158 
00164       bool 
00165       doSamplesVerifyModel (const std::set<int> &indices, 
00166                             const Eigen::VectorXf &model_coefficients, 
00167                             const double threshold);
00168 
00170       inline pcl::SacModel getModelType () const { return (SACMODEL_SPHERE); }
00171 
00172     protected:
00176       inline bool 
00177       isModelValid (const Eigen::VectorXf &model_coefficients)
00178       {
00179         // Needs a valid model coefficients
00180         if (model_coefficients.size () != 4)
00181         {
00182           PCL_ERROR ("[pcl::SampleConsensusModelSphere::isModelValid] Invalid number of model coefficients given (%lu)!\n", (unsigned long)model_coefficients.size ());
00183           return (false);
00184         }
00185 
00186         if (radius_min_ != -DBL_MAX && model_coefficients[3] < radius_min_)
00187           return (false);
00188         if (radius_max_ != DBL_MAX && model_coefficients[3] > radius_max_)
00189           return (false);
00190 
00191         return (true);
00192       }
00193 
00198       bool
00199       isSampleGood(const std::vector<int> &samples) const;
00200 
00201     private:
00203       const std::vector<int> *tmp_inliers_;
00204 
00205       struct OptimizationFunctor : pcl::Functor<float>
00206       {
00212         OptimizationFunctor (int m_data_points, pcl::SampleConsensusModelSphere<PointT> *model) : 
00213           pcl::Functor<float>(m_data_points), model_ (model) {}
00214 
00220         int 
00221         operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
00222         {
00223           Eigen::Vector4f cen_t;
00224           cen_t[3] = 0;
00225           for (int i = 0; i < values (); ++i)
00226           {
00227             // Compute the difference between the center of the sphere and the datapoint X_i
00228             cen_t[0] = model_->input_->points[(*model_->tmp_inliers_)[i]].x - x[0];
00229             cen_t[1] = model_->input_->points[(*model_->tmp_inliers_)[i]].y - x[1];
00230             cen_t[2] = model_->input_->points[(*model_->tmp_inliers_)[i]].z - x[2];
00231             
00232             // g = sqrt ((x-a)^2 + (y-b)^2 + (z-c)^2) - R
00233             fvec[i] = sqrt (cen_t.dot (cen_t)) - x[3];
00234           }
00235           return (0);
00236         }
00237         
00238         pcl::SampleConsensusModelSphere<PointT> *model_;
00239       };
00240   };
00241 }
00242 
00243 #endif  //#ifndef PCL_SAMPLE_CONSENSUS_MODEL_SPHERE_H_