sac_model_sphere.h

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 * $Id: sac_model_sphere.h 3751 2011-12-31 23:18:12Z rusu $
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#ifndef PCL_SAMPLE_CONSENSUS_MODEL_SPHERE_H_
#define PCL_SAMPLE_CONSENSUS_MODEL_SPHERE_H_

#include <pcl/sample_consensus/sac_model.h>
#include <pcl/sample_consensus/model_types.h>
#include <boost/thread/mutex.hpp>

namespace pcl
{
  template <typename PointT>
  class SampleConsensusModelSphere : public SampleConsensusModel<PointT>
  {
    using SampleConsensusModel<PointT>::input_;
    using SampleConsensusModel<PointT>::indices_;
    using SampleConsensusModel<PointT>::radius_min_;
    using SampleConsensusModel<PointT>::radius_max_;

    public:
      typedef typename SampleConsensusModel<PointT>::PointCloud PointCloud;
      typedef typename SampleConsensusModel<PointT>::PointCloudPtr PointCloudPtr;
      typedef typename SampleConsensusModel<PointT>::PointCloudConstPtr PointCloudConstPtr;

      typedef boost::shared_ptr<SampleConsensusModelSphere> Ptr;

      SampleConsensusModelSphere (const PointCloudConstPtr &cloud) : SampleConsensusModel<PointT> (cloud) { }

      SampleConsensusModelSphere (const PointCloudConstPtr &cloud, const std::vector<int> &indices) : SampleConsensusModel<PointT> (cloud, indices) { }

      void 
      getSamples (int &iterations, std::vector<int> &samples);

      bool 
      computeModelCoefficients (const std::vector<int> &samples, 
                                Eigen::VectorXf &model_coefficients);

      void 
      getDistancesToModel (const Eigen::VectorXf &model_coefficients, 
                           std::vector<double> &distances);

      void 
      selectWithinDistance (const Eigen::VectorXf &model_coefficients, 
                            const double threshold, 
                            std::vector<int> &inliers);

      virtual int
      countWithinDistance (const Eigen::VectorXf &model_coefficients, 
                           const double threshold);

      void 
      optimizeModelCoefficients (const std::vector<int> &inliers, 
                                 const Eigen::VectorXf &model_coefficients, 
                                 Eigen::VectorXf &optimized_coefficients);

      void 
      projectPoints (const std::vector<int> &inliers, 
                     const Eigen::VectorXf &model_coefficients, 
                     PointCloud &projected_points, 
                     bool copy_data_fields = true);

      bool 
      doSamplesVerifyModel (const std::set<int> &indices, 
                            const Eigen::VectorXf &model_coefficients, 
                            const double threshold);

      inline pcl::SacModel getModelType () const { return (SACMODEL_SPHERE); }

    protected:
      inline bool 
      isModelValid (const Eigen::VectorXf &model_coefficients)
      {
        // Needs a valid model coefficients
        if (model_coefficients.size () != 4)
        {
          PCL_ERROR ("[pcl::SampleConsensusModelSphere::isModelValid] Invalid number of model coefficients given (%lu)!\n", (unsigned long)model_coefficients.size ());
          return (false);
        }

        if (radius_min_ != -DBL_MAX && model_coefficients[3] < radius_min_)
          return (false);
        if (radius_max_ != DBL_MAX && model_coefficients[3] > radius_max_)
          return (false);

        return (true);
      }

      bool
      isSampleGood(const std::vector<int> &samples) const;

    private:
      boost::mutex tmp_mutex_;

      const std::vector<int> *tmp_inliers_;

      struct OptimizationFunctor : pcl::Functor<double>
      {
        OptimizationFunctor(int n, int m, pcl::SampleConsensusModelSphere<PointT> *model) : 
          pcl::Functor<double>(m,n), model_(model) {}
        int operator() (const Eigen::VectorXd &x, Eigen::VectorXd &fvec) const
        {
          Eigen::Vector4d cen_t;
          cen_t[3] = 0;
          for (int i = 0; i < m_values; ++i)
          {
            // Compute the difference between the center of the sphere and the datapoint X_i
            cen_t[0] = model_->input_->points[(*model_->tmp_inliers_)[i]].x - x[0];
            cen_t[1] = model_->input_->points[(*model_->tmp_inliers_)[i]].y - x[1];
            cen_t[2] = model_->input_->points[(*model_->tmp_inliers_)[i]].z - x[2];
            
            // g = sqrt ((x-a)^2 + (y-b)^2 + (z-c)^2) - R
            fvec[i] = sqrt (cen_t.dot (cen_t)) - x[3];
          }
          return (0);
        }
        
        pcl::SampleConsensusModelSphere<PointT> *model_;
      };
  };
}

#endif  //#ifndef PCL_SAMPLE_CONSENSUS_MODEL_SPHERE_H_