Point Cloud Library (PCL)  1.9.1
lmeds.h
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40 
41 #ifndef PCL_SAMPLE_CONSENSUS_LMEDS_H_
42 #define PCL_SAMPLE_CONSENSUS_LMEDS_H_
43 
44 #include <pcl/sample_consensus/sac.h>
45 #include <pcl/sample_consensus/sac_model.h>
46 
47 namespace pcl
48 {
49  /** \brief @b LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm. LMedS
50  * is a RANSAC-like model-fitting algorithm that can tolerate up to 50% outliers without requiring thresholds to be
51  * set. See Andrea Fusiello's "Elements of Geometric Computer Vision"
52  * (http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/FUSIELLO4/tutorial.html#x1-520007) for more details.
53  * \author Radu B. Rusu
54  * \ingroup sample_consensus
55  */
56  template <typename PointT>
57  class LeastMedianSquares : public SampleConsensus<PointT>
58  {
59  typedef typename SampleConsensusModel<PointT>::Ptr SampleConsensusModelPtr;
60 
61  public:
62  typedef boost::shared_ptr<LeastMedianSquares> Ptr;
63  typedef boost::shared_ptr<const LeastMedianSquares> ConstPtr;
64 
72 
73  /** \brief LMedS (Least Median of Squares) main constructor
74  * \param[in] model a Sample Consensus model
75  */
76  LeastMedianSquares (const SampleConsensusModelPtr &model)
77  : SampleConsensus<PointT> (model)
78  {
79  // Maximum number of trials before we give up.
80  max_iterations_ = 50;
81  }
82 
83  /** \brief LMedS (Least Median of Squares) main constructor
84  * \param[in] model a Sample Consensus model
85  * \param[in] threshold distance to model threshold
86  */
87  LeastMedianSquares (const SampleConsensusModelPtr &model, double threshold)
88  : SampleConsensus<PointT> (model, threshold)
89  {
90  // Maximum number of trials before we give up.
91  max_iterations_ = 50;
92  }
93 
94  /** \brief Compute the actual model and find the inliers
95  * \param[in] debug_verbosity_level enable/disable on-screen debug information and set the verbosity level
96  */
97  bool
98  computeModel (int debug_verbosity_level = 0);
99  };
100 }
101 
102 #ifdef PCL_NO_PRECOMPILE
103 #include <pcl/sample_consensus/impl/lmeds.hpp>
104 #endif
105 
106 #endif //#ifndef PCL_SAMPLE_CONSENSUS_LMEDS_H_
107 
pcl
This file defines compatibility wrappers for low level I/O functions.
Definition: convolution.h:45
pcl::LeastMedianSquares::LeastMedianSquares
LeastMedianSquares(const SampleConsensusModelPtr &model)
LMedS (Least Median of Squares) main constructor.
Definition: lmeds.h:76
pcl::SampleConsensusModel::Ptr
boost::shared_ptr< SampleConsensusModel > Ptr
Definition: sac_model.h:74
pcl::LeastMedianSquares::ConstPtr
boost::shared_ptr< const LeastMedianSquares > ConstPtr
Definition: lmeds.h:63
pcl::PointXYZRGB
A point structure representing Euclidean xyz coordinates, and the RGB color.
Definition: point_types.hpp:619
pcl::LeastMedianSquares
LeastMedianSquares represents an implementation of the LMedS (Least Median of Squares) algorithm.
Definition: lmeds.h:57
pcl::LeastMedianSquares::computeModel
bool computeModel(int debug_verbosity_level=0)
Compute the actual model and find the inliers.
Definition: lmeds.hpp:48
pcl::SampleConsensus
SampleConsensus represents the base class.
Definition: sac.h:56
pcl::LeastMedianSquares::Ptr
boost::shared_ptr< LeastMedianSquares > Ptr
Definition: lmeds.h:62
pcl::SampleConsensus< PointT >::max_iterations_
int max_iterations_
Maximum number of iterations before giving up.
Definition: sac.h:331
pcl::LeastMedianSquares::LeastMedianSquares
LeastMedianSquares(const SampleConsensusModelPtr &model, double threshold)
LMedS (Least Median of Squares) main constructor.
Definition: lmeds.h:87