Point Cloud Library (PCL) 1.12.0
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rmsac.h
1/*
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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
46namespace 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
Eigen::VectorXf model_coefficients_
Definition sac.h:329
SampleConsensusModelPtr sac_model_
Definition sac.h:320
shared_ptr< SampleConsensusModel< PointT > > Ptr
Definition sac_model.h:77
A point structure representing Euclidean xyz coordinates, and the RGB color.