Point Cloud Library (PCL)  1.12.1-dev
ransac.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 RandomSampleConsensus represents an implementation of the RANSAC (RANdom SAmple Consensus) algorithm, as
49  * described in: "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and
50  * Automated Cartography", Martin A. Fischler and Robert C. Bolles, Comm. Of the ACM 24: 381–395, June 1981.
51  * A parallel variant is available, enable with setNumberOfThreads. Default is non-parallel.
52  *
53  * The algorithm works as follows:
54  * <ol>
55  * <li> randomly select samples from the cloud, just as many as needed to determine a model
56  * <li> compute the coefficients of the model from the samples
57  * <li> count how many points of the cloud belong to the model, given a threshold. These are called inliers
58  * <li> repeat until a good model has been found or a max number of iterations has been reached
59  * <li> return the model with the most inliers
60  * </ol>
61  * \author Radu B. Rusu
62  * \ingroup sample_consensus
63  */
64  template <typename PointT>
65  class RandomSampleConsensus : public SampleConsensus<PointT>
66  {
67  using SampleConsensusModelPtr = typename SampleConsensusModel<PointT>::Ptr;
68 
69  public:
70  using Ptr = shared_ptr<RandomSampleConsensus<PointT> >;
71  using ConstPtr = shared_ptr<const RandomSampleConsensus<PointT> >;
72 
82 
83  /** \brief RANSAC (RANdom SAmple Consensus) main constructor
84  * \param[in] model a Sample Consensus model
85  */
86  RandomSampleConsensus (const SampleConsensusModelPtr &model)
87  : SampleConsensus<PointT> (model)
88  {
89  // Maximum number of trials before we give up.
90  max_iterations_ = 10000;
91  }
92 
93  /** \brief RANSAC (RANdom SAmple Consensus) main constructor
94  * \param[in] model a Sample Consensus model
95  * \param[in] threshold distance to model threshold
96  */
97  RandomSampleConsensus (const SampleConsensusModelPtr &model, double threshold)
98  : SampleConsensus<PointT> (model, threshold)
99  {
100  // Maximum number of trials before we give up.
101  max_iterations_ = 10000;
102  }
103 
104  /** \brief Compute the actual model and find the inliers
105  * \param[in] debug_verbosity_level enable/disable on-screen debug information and set the verbosity level
106  */
107  bool
108  computeModel (int debug_verbosity_level = 0) override;
109  };
110 }
111 
112 #ifdef PCL_NO_PRECOMPILE
113 #include <pcl/sample_consensus/impl/ransac.hpp>
114 #endif
RandomSampleConsensus represents an implementation of the RANSAC (RANdom SAmple Consensus) algorithm,...
Definition: ransac.h:66
shared_ptr< RandomSampleConsensus< PointT > > Ptr
Definition: ransac.h:70
bool computeModel(int debug_verbosity_level=0) override
Compute the actual model and find the inliers.
Definition: ransac.hpp:57
shared_ptr< const RandomSampleConsensus< PointT > > ConstPtr
Definition: ransac.h:71
RandomSampleConsensus(const SampleConsensusModelPtr &model)
RANSAC (RANdom SAmple Consensus) main constructor.
Definition: ransac.h:86
RandomSampleConsensus(const SampleConsensusModelPtr &model, double threshold)
RANSAC (RANdom SAmple Consensus) main constructor.
Definition: ransac.h:97
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.