Point Cloud Library (PCL)  1.14.0-dev
rmsac.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 RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized M-estimator
49  * SAmple Consensus) algorithm, which basically adds a Td,d test (see \a RandomizedRandomSampleConsensus) to an MSAC
50  * estimator (see \a MEstimatorSampleConsensus).
51  * \note RMSAC is useful in situations where most of the data samples belong to the model, and a fast outlier rejection algorithm is needed.
52  * \author Radu B. Rusu
53  * \ingroup sample_consensus
54  */
55  template <typename PointT>
57  {
58  using SampleConsensusModelPtr = typename SampleConsensusModel<PointT>::Ptr;
59 
60  public:
61  using Ptr = shared_ptr<RandomizedMEstimatorSampleConsensus<PointT> >;
62  using ConstPtr = shared_ptr<const RandomizedMEstimatorSampleConsensus<PointT> >;
63 
72 
73  /** \brief RMSAC (Randomized M-estimator SAmple Consensus) main constructor
74  * \param[in] model a Sample Consensus model
75  */
76  RandomizedMEstimatorSampleConsensus (const SampleConsensusModelPtr &model)
77  : SampleConsensus<PointT> (model)
78  , fraction_nr_pretest_ (10.0) // Number of samples to try randomly in percents
79  {
80  // Maximum number of trials before we give up.
81  max_iterations_ = 10000;
82  }
83 
84  /** \brief RMSAC (Randomized M-estimator SAmple Consensus) main constructor
85  * \param[in] model a Sample Consensus model
86  * \param[in] threshold distance to model threshold
87  */
88  RandomizedMEstimatorSampleConsensus (const SampleConsensusModelPtr &model, double threshold)
89  : SampleConsensus<PointT> (model, threshold)
90  , fraction_nr_pretest_ (10.0) // Number of samples to try randomly in percents
91  {
92  // Maximum number of trials before we give up.
93  max_iterations_ = 10000;
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  /** \brief Set the percentage of points to pre-test.
103  * \param[in] nr_pretest percentage of points to pre-test
104  */
105  inline void
106  setFractionNrPretest (double nr_pretest) { fraction_nr_pretest_ = nr_pretest; }
107 
108  /** \brief Get the percentage of points to pre-test. */
109  inline double
110  getFractionNrPretest () const { return (fraction_nr_pretest_); }
111 
112  private:
113  /** \brief Number of samples to randomly pre-test, in percents. */
114  double fraction_nr_pretest_;
115  };
116 }
117 
118 #ifdef PCL_NO_PRECOMPILE
119 #include <pcl/sample_consensus/impl/rmsac.hpp>
120 #endif
RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized M-estimator...
Definition: rmsac.h:57
shared_ptr< const RandomizedMEstimatorSampleConsensus< PointT > > ConstPtr
Definition: rmsac.h:62
RandomizedMEstimatorSampleConsensus(const SampleConsensusModelPtr &model, double threshold)
RMSAC (Randomized M-estimator SAmple Consensus) main constructor.
Definition: rmsac.h:88
bool computeModel(int debug_verbosity_level=0) override
Compute the actual model and find the inliers.
Definition: rmsac.hpp:48
shared_ptr< RandomizedMEstimatorSampleConsensus< PointT > > Ptr
Definition: rmsac.h:61
RandomizedMEstimatorSampleConsensus(const SampleConsensusModelPtr &model)
RMSAC (Randomized M-estimator SAmple Consensus) main constructor.
Definition: rmsac.h:76
double getFractionNrPretest() const
Get the percentage of points to pre-test.
Definition: rmsac.h:110
void setFractionNrPretest(double nr_pretest)
Set the percentage of points to pre-test.
Definition: rmsac.h:106
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:78
A point structure representing Euclidean xyz coordinates, and the RGB color.