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 * $Id: lmeds.h 1370 2011-06-19 01:06:01Z jspricke $
 *
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#ifndef PCL_SAMPLE_CONSENSUS_LMEDS_H_
#define PCL_SAMPLE_CONSENSUS_LMEDS_H_

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

namespace pcl
{
  //////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
  /** \brief @b LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm. LMedS 
    * is a RANSAC-like model-fitting algorithm that can tolerate up to 50% outliers without requiring thresholds to be 
    * set. See Andrea Fusiello's "Elements of Geometric Computer Vision"
    * (http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/FUSIELLO4/tutorial.html#x1-520007) for more details.
    * \author Radu Bogdan Rusu
    * \ingroup sample_consensus
    */
  template <typename PointT>
  class LeastMedianSquares : public SampleConsensus<PointT>
  {
    using SampleConsensus<PointT>::max_iterations_;
    using SampleConsensus<PointT>::threshold_;
    using SampleConsensus<PointT>::iterations_;
    using SampleConsensus<PointT>::sac_model_;
    using SampleConsensus<PointT>::model_;
    using SampleConsensus<PointT>::model_coefficients_;
    using SampleConsensus<PointT>::inliers_;

    typedef typename SampleConsensusModel<PointT>::Ptr SampleConsensusModelPtr;

    public:
      /** \brief LMedS (Least Median of Squares) main constructor
        * \param model a Sample Consensus model
        */
      LeastMedianSquares (const SampleConsensusModelPtr &model) : SampleConsensus<PointT> (model)
      {
        // Maximum number of trials before we give up.
        max_iterations_ = 50;
      }

      /** \brief LMedS (Least Median of Squares) main constructor
        * \param model a Sample Consensus model
        * \param threshold distance to model threshold
        */
      LeastMedianSquares (const SampleConsensusModelPtr &model, double threshold) : SampleConsensus<PointT> (model, threshold)
      {
        // Maximum number of trials before we give up.
        max_iterations_ = 50;
      }

      /** \brief Compute the actual model and find the inliers
        * \param debug_verbosity_level enable/disable on-screen debug information and set the verbosity level
        */
      bool computeModel (int debug_verbosity_level = 0);
  };
}

#endif  //#ifndef PCL_SAMPLE_CONSENSUS_LMEDS_H_

