Point Cloud Library (PCL)  1.12.1-dev
lmeds.h
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40 
41 #pragma once
42 
43 #include <pcl/sample_consensus/sac.h>
44 #include <pcl/sample_consensus/sac_model.h>
45 
46 namespace pcl
47 {
48  /** \brief @b LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm. LMedS
49  * is a RANSAC-like model-fitting algorithm that can tolerate up to 50% outliers without requiring thresholds to be
50  * set. See Andrea Fusiello's "Elements of Geometric Computer Vision"
51  * (http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/FUSIELLO4/tutorial.html#x1-520007) for more details.
52  * In contrast to RANSAC, LMedS does not divide the points into inliers and outliers when finding the model. Instead,
53  * it uses the median of all point-model distances as the measure of how good a model is. A threshold is only needed
54  * at the end, when it is determined which points belong to the found model.
55  * \author Radu B. Rusu
56  * \ingroup sample_consensus
57  */
58  template <typename PointT>
59  class LeastMedianSquares : public SampleConsensus<PointT>
60  {
61  using SampleConsensusModelPtr = typename SampleConsensusModel<PointT>::Ptr;
62 
63  public:
64  using Ptr = shared_ptr<LeastMedianSquares<PointT> >;
65  using ConstPtr = shared_ptr<const LeastMedianSquares<PointT> >;
66 
74 
75  /** \brief LMedS (Least Median of Squares) main constructor
76  * \param[in] model a Sample Consensus model
77  */
78  LeastMedianSquares (const SampleConsensusModelPtr &model)
79  : SampleConsensus<PointT> (model)
80  {
81  // Maximum number of trials before we give up.
82  max_iterations_ = 50;
83  }
84 
85  /** \brief LMedS (Least Median of Squares) main constructor
86  * \param[in] model a Sample Consensus model
87  * \param[in] threshold distance to model threshold
88  */
89  LeastMedianSquares (const SampleConsensusModelPtr &model, double threshold)
90  : SampleConsensus<PointT> (model, threshold)
91  {
92  // Maximum number of trials before we give up.
93  max_iterations_ = 50;
94  }
95 
96  /** \brief Compute the actual model and find the inliers
97  * \param[in] debug_verbosity_level enable/disable on-screen debug information and set the verbosity level
98  */
99  bool
100  computeModel (int debug_verbosity_level = 0) override;
101  };
102 }
103 
104 #ifdef PCL_NO_PRECOMPILE
105 #include <pcl/sample_consensus/impl/lmeds.hpp>
106 #endif
LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm.
Definition: lmeds.h:60
LeastMedianSquares(const SampleConsensusModelPtr &model)
LMedS (Least Median of Squares) main constructor.
Definition: lmeds.h:78
LeastMedianSquares(const SampleConsensusModelPtr &model, double threshold)
LMedS (Least Median of Squares) main constructor.
Definition: lmeds.h:89
shared_ptr< LeastMedianSquares< PointT > > Ptr
Definition: lmeds.h:64
shared_ptr< const LeastMedianSquares< PointT > > ConstPtr
Definition: lmeds.h:65
bool computeModel(int debug_verbosity_level=0) override
Compute the actual model and find the inliers.
Definition: lmeds.hpp:49
SampleConsensus represents the base class.
Definition: sac.h:61
int max_iterations_
Maximum number of iterations before giving up.
Definition: sac.h:341
shared_ptr< SampleConsensusModel< PointT > > Ptr
Definition: sac_model.h:77
A point structure representing Euclidean xyz coordinates, and the RGB color.