Point Cloud Library (PCL)  1.9.1
rmsac.h
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40 
41 #ifndef PCL_SAMPLE_CONSENSUS_RMSAC_H_
42 #define PCL_SAMPLE_CONSENSUS_RMSAC_H_
43 
44 #include <algorithm>
45 #include <pcl/sample_consensus/sac.h>
46 #include <pcl/sample_consensus/sac_model.h>
47 
48 namespace pcl
49 {
50  /** \brief @b RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized M-estimator
51  * SAmple Consensus) algorithm, which basically adds a Td,d test (see \a RandomizedRandomSampleConsensus) to an MSAC
52  * estimator (see \a MEstimatorSampleConsensus).
53  * \note RMSAC is useful in situations where most of the data samples belong to the model, and a fast outlier rejection algorithm is needed.
54  * \author Radu B. Rusu
55  * \ingroup sample_consensus
56  */
57  template <typename PointT>
59  {
60  typedef typename SampleConsensusModel<PointT>::Ptr SampleConsensusModelPtr;
61 
62  public:
63  typedef boost::shared_ptr<RandomizedMEstimatorSampleConsensus> Ptr;
64  typedef boost::shared_ptr<const RandomizedMEstimatorSampleConsensus> ConstPtr;
65 
74 
75  /** \brief RMSAC (Randomized M-estimator SAmple Consensus) main constructor
76  * \param[in] model a Sample Consensus model
77  */
78  RandomizedMEstimatorSampleConsensus (const SampleConsensusModelPtr &model)
79  : SampleConsensus<PointT> (model)
80  , fraction_nr_pretest_ (10.0) // Number of samples to try randomly in percents
81  {
82  // Maximum number of trials before we give up.
83  max_iterations_ = 10000;
84  }
85 
86  /** \brief RMSAC (Randomized M-estimator SAmple Consensus) main constructor
87  * \param[in] model a Sample Consensus model
88  * \param[in] threshold distance to model threshold
89  */
90  RandomizedMEstimatorSampleConsensus (const SampleConsensusModelPtr &model, double threshold)
91  : SampleConsensus<PointT> (model, threshold)
92  , fraction_nr_pretest_ (10.0) // Number of samples to try randomly in percents
93  {
94  // Maximum number of trials before we give up.
95  max_iterations_ = 10000;
96  }
97 
98  /** \brief Compute the actual model and find the inliers
99  * \param[in] debug_verbosity_level enable/disable on-screen debug information and set the verbosity level
100  */
101  bool
102  computeModel (int debug_verbosity_level = 0);
103 
104  /** \brief Set the percentage of points to pre-test.
105  * \param[in] nr_pretest percentage of points to pre-test
106  */
107  inline void
108  setFractionNrPretest (double nr_pretest) { fraction_nr_pretest_ = nr_pretest; }
109 
110  /** \brief Get the percentage of points to pre-test. */
111  inline double
112  getFractionNrPretest () { return (fraction_nr_pretest_); }
113 
114  private:
115  /** \brief Number of samples to randomly pre-test, in percents. */
116  double fraction_nr_pretest_;
117  };
118 }
119 
120 #ifdef PCL_NO_PRECOMPILE
121 #include <pcl/sample_consensus/impl/rmsac.hpp>
122 #endif
123 
124 #endif //#ifndef PCL_SAMPLE_CONSENSUS_RMSAC_H_
pcl
This file defines compatibility wrappers for low level I/O functions.
Definition: convolution.h:45
pcl::SampleConsensusModel::Ptr
boost::shared_ptr< SampleConsensusModel > Ptr
Definition: sac_model.h:74
pcl::RandomizedMEstimatorSampleConsensus::RandomizedMEstimatorSampleConsensus
RandomizedMEstimatorSampleConsensus(const SampleConsensusModelPtr &model)
RMSAC (Randomized M-estimator SAmple Consensus) main constructor.
Definition: rmsac.h:78
pcl::PointXYZRGB
A point structure representing Euclidean xyz coordinates, and the RGB color.
Definition: point_types.hpp:619
pcl::RandomizedMEstimatorSampleConsensus::setFractionNrPretest
void setFractionNrPretest(double nr_pretest)
Set the percentage of points to pre-test.
Definition: rmsac.h:108
pcl::RandomizedMEstimatorSampleConsensus::computeModel
bool computeModel(int debug_verbosity_level=0)
Compute the actual model and find the inliers.
Definition: rmsac.hpp:48
pcl::RandomizedMEstimatorSampleConsensus::RandomizedMEstimatorSampleConsensus
RandomizedMEstimatorSampleConsensus(const SampleConsensusModelPtr &model, double threshold)
RMSAC (Randomized M-estimator SAmple Consensus) main constructor.
Definition: rmsac.h:90
pcl::RandomizedMEstimatorSampleConsensus
RandomizedMEstimatorSampleConsensus represents an implementation of the RMSAC (Randomized M-estimator...
Definition: rmsac.h:58
pcl::SampleConsensus
SampleConsensus represents the base class.
Definition: sac.h:56
pcl::RandomizedMEstimatorSampleConsensus::ConstPtr
boost::shared_ptr< const RandomizedMEstimatorSampleConsensus > ConstPtr
Definition: rmsac.h:64
pcl::RandomizedMEstimatorSampleConsensus::getFractionNrPretest
double getFractionNrPretest()
Get the percentage of points to pre-test.
Definition: rmsac.h:112
pcl::SampleConsensus< PointT >::max_iterations_
int max_iterations_
Maximum number of iterations before giving up.
Definition: sac.h:331
pcl::RandomizedMEstimatorSampleConsensus::Ptr
boost::shared_ptr< RandomizedMEstimatorSampleConsensus > Ptr
Definition: rmsac.h:63