lmeds.h

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#pragma once
 
#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.
    * In contrast to RANSAC, LMedS does not divide the points into inliers and outliers when finding the model. Instead,
    * it uses the median of all point-model distances as the measure of how good a model is. A threshold is only needed
    * at the end, when it is determined which points belong to the found model.
    * \author Radu B. Rusu
    * \ingroup sample_consensus
    */
  template <typename PointT>
  class LeastMedianSquares : public SampleConsensus<PointT>
  {
    using SampleConsensusModelPtr = typename SampleConsensusModel<PointT>::Ptr;
 
    public:
      using Ptr = shared_ptr<LeastMedianSquares<PointT> >;
      using ConstPtr = shared_ptr<const LeastMedianSquares<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_;
 
      /** \brief LMedS (Least Median of Squares) main constructor
        * \param[in] 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[in] model a Sample Consensus model
        * \param[in] 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[in] debug_verbosity_level enable/disable on-screen debug information and set the verbosity level
        */
      bool 
      computeModel (int debug_verbosity_level = 0) override;
  };
}
 
#ifdef PCL_NO_PRECOMPILE
#include <pcl/sample_consensus/impl/lmeds.hpp>
#endif