sac_model_sphere.h

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00001 /*
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00036  * $Id: sac_model_sphere.h 3027 2011-11-01 04:04:27Z rusu $
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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 #include <boost/thread/mutex.hpp>
00046 
00047 namespace pcl
00048 {
00060   template <typename PointT>
00061   class SampleConsensusModelSphere : public SampleConsensusModel<PointT>
00062   {
00063     using SampleConsensusModel<PointT>::input_;
00064     using SampleConsensusModel<PointT>::indices_;
00065     using SampleConsensusModel<PointT>::radius_min_;
00066     using SampleConsensusModel<PointT>::radius_max_;
00067 
00068     public:
00069       typedef typename SampleConsensusModel<PointT>::PointCloud PointCloud;
00070       typedef typename SampleConsensusModel<PointT>::PointCloudPtr PointCloudPtr;
00071       typedef typename SampleConsensusModel<PointT>::PointCloudConstPtr PointCloudConstPtr;
00072 
00073       typedef boost::shared_ptr<SampleConsensusModelSphere> Ptr;
00074 
00078       SampleConsensusModelSphere (const PointCloudConstPtr &cloud) : SampleConsensusModel<PointT> (cloud) { }
00079 
00084       SampleConsensusModelSphere (const PointCloudConstPtr &cloud, const std::vector<int> &indices) : SampleConsensusModel<PointT> (cloud, indices) { }
00085 
00096       void 
00097       getSamples (int &iterations, std::vector<int> &samples);
00098 
00105       bool 
00106       computeModelCoefficients (const std::vector<int> &samples, 
00107                                 Eigen::VectorXf &model_coefficients);
00108 
00113       void 
00114       getDistancesToModel (const Eigen::VectorXf &model_coefficients, 
00115                            std::vector<double> &distances);
00116 
00122       void 
00123       selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
00124                             const double threshold, 
00125                             std::vector<int> &inliers);
00126 
00133       virtual int
00134       countWithinDistance (const Eigen::VectorXf &model_coefficients, 
00135                            const double threshold);
00136 
00143       void 
00144       optimizeModelCoefficients (const std::vector<int> &inliers, 
00145                                  const Eigen::VectorXf &model_coefficients, 
00146                                  Eigen::VectorXf &optimized_coefficients);
00147 
00155       void 
00156       projectPoints (const std::vector<int> &inliers, 
00157                      const Eigen::VectorXf &model_coefficients, 
00158                      PointCloud &projected_points, 
00159                      bool copy_data_fields = true);
00160 
00166       bool 
00167       doSamplesVerifyModel (const std::set<int> &indices, 
00168                             const Eigen::VectorXf &model_coefficients, 
00169                             const double threshold);
00170 
00172       inline pcl::SacModel getModelType () const { return (SACMODEL_SPHERE); }
00173 
00174     protected:
00178       inline bool 
00179       isModelValid (const Eigen::VectorXf &model_coefficients)
00180       {
00181         // Needs a valid model coefficients
00182         if (model_coefficients.size () != 4)
00183         {
00184           PCL_ERROR ("[pcl::SampleConsensusModelSphere::isModelValid] Invalid number of model coefficients given (%lu)!\n", (unsigned long)model_coefficients.size ());
00185           return (false);
00186         }
00187 
00188         if (radius_min_ != -DBL_MAX && model_coefficients[3] < radius_min_)
00189           return (false);
00190         if (radius_max_ != DBL_MAX && model_coefficients[3] > radius_max_)
00191           return (false);
00192 
00193         return (true);
00194       }
00195 
00200       bool
00201       isSampleGood(const std::vector<int> &samples) const;
00202 
00203     private:
00205       boost::mutex tmp_mutex_;
00206 
00208       const std::vector<int> *tmp_inliers_;
00209 
00210       struct OptimizationFunctor : pcl::Functor<double>
00211       {
00218         OptimizationFunctor(int n, int m, pcl::SampleConsensusModelSphere<PointT> *model) : 
00219           pcl::Functor<double>(m,n), model_(model) {}
00225         int operator() (const Eigen::VectorXd &x, Eigen::VectorXd &fvec) const
00226         {
00227           Eigen::Vector4d cen_t;
00228           cen_t[3] = 0;
00229           for (int i = 0; i < m_values; ++i)
00230           {
00231             // Compute the difference between the center of the sphere and the datapoint X_i
00232             cen_t[0] = model_->input_->points[(*model_->tmp_inliers_)[i]].x - x[0];
00233             cen_t[1] = model_->input_->points[(*model_->tmp_inliers_)[i]].y - x[1];
00234             cen_t[2] = model_->input_->points[(*model_->tmp_inliers_)[i]].z - x[2];
00235             
00236             // g = sqrt ((x-a)^2 + (y-b)^2 + (z-c)^2) - R
00237             fvec[i] = sqrt (cen_t.dot (cen_t)) - x[3];
00238           }
00239           return (0);
00240         }
00241         
00242         pcl::SampleConsensusModelSphere<PointT> *model_;
00243       };
00244   };
00245 }
00246 
00247 #endif  //#ifndef PCL_SAMPLE_CONSENSUS_MODEL_SPHERE_H_