sac_model_circle.h

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 * $Id: sac_model_circle.h 4702 2012-02-23 09:39:33Z gedikli $
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#ifndef PCL_SAMPLE_CONSENSUS_MODEL_CIRCLE2D_H_
#define PCL_SAMPLE_CONSENSUS_MODEL_CIRCLE2D_H_

#include <pcl/sample_consensus/sac_model.h>
#include <pcl/sample_consensus/model_types.h>

namespace pcl
{
  template <typename PointT>
  class SampleConsensusModelCircle2D : 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<SampleConsensusModelCircle2D> Ptr;

      SampleConsensusModelCircle2D (const PointCloudConstPtr &cloud) : SampleConsensusModel<PointT> (cloud) {};

      SampleConsensusModelCircle2D (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_CIRCLE2D); }

    protected:
      bool 
      isModelValid (const Eigen::VectorXf &model_coefficients);

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

    private:
      const std::vector<int> *tmp_inliers_;

      struct OptimizationFunctor : pcl::Functor<float>
      {
        OptimizationFunctor (int m_data_points, pcl::SampleConsensusModelCircle2D<PointT> *model) : 
          pcl::Functor<float>(m_data_points), model_ (model) {}

        int 
        operator() (const Eigen::VectorXf &x, Eigen::VectorXf &fvec) const
        {
          for (int i = 0; i < values (); ++i)
          {
            // Compute the difference between the center of the circle and the datapoint X_i
            float xt = model_->input_->points[(*model_->tmp_inliers_)[i]].x - x[0];
            float yt = model_->input_->points[(*model_->tmp_inliers_)[i]].y - x[1];
            
            // g = sqrt ((x-a)^2 + (y-b)^2) - R
            fvec[i] = sqrt (xt * xt + yt * yt) - x[2];
          }
          return (0);
        }

        pcl::SampleConsensusModelCircle2D<PointT> *model_;
      };
  };
}

#endif  //#ifndef PCL_SAMPLE_CONSENSUS_MODEL_CIRCLE2D_H_