Point Cloud Library (PCL)  1.9.1
msac.h
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40 
41 #ifndef PCL_SAMPLE_CONSENSUS_MSAC_H_
42 #define PCL_SAMPLE_CONSENSUS_MSAC_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 MEstimatorSampleConsensus represents an implementation of the MSAC (M-estimator SAmple Consensus)
51  * algorithm, as described in: "MLESAC: A new robust estimator with application to estimating image geometry", P.H.S.
52  * Torr and A. Zisserman, Computer Vision and Image Understanding, vol 78, 2000.
53  * \author Radu B. Rusu
54  * \ingroup sample_consensus
55  */
56  template <typename PointT>
58  {
59  typedef typename SampleConsensusModel<PointT>::Ptr SampleConsensusModelPtr;
60 
61  public:
62  typedef boost::shared_ptr<MEstimatorSampleConsensus> Ptr;
63  typedef boost::shared_ptr<const MEstimatorSampleConsensus> ConstPtr;
64 
73 
74  /** \brief MSAC (M-estimator SAmple Consensus) main constructor
75  * \param[in] model a Sample Consensus model
76  */
77  MEstimatorSampleConsensus (const SampleConsensusModelPtr &model)
78  : SampleConsensus<PointT> (model)
79  {
80  // Maximum number of trials before we give up.
81  max_iterations_ = 10000;
82  }
83 
84  /** \brief MSAC (M-estimator SAmple Consensus) main constructor
85  * \param[in] model a Sample Consensus model
86  * \param[in] threshold distance to model threshold
87  */
88  MEstimatorSampleConsensus (const SampleConsensusModelPtr &model, double threshold)
89  : SampleConsensus<PointT> (model, threshold)
90  {
91  // Maximum number of trials before we give up.
92  max_iterations_ = 10000;
93  }
94 
95  /** \brief Compute the actual model and find the inliers
96  * \param[in] debug_verbosity_level enable/disable on-screen debug information and set the verbosity level
97  */
98  bool
99  computeModel (int debug_verbosity_level = 0);
100  };
101 }
102 
103 #ifdef PCL_NO_PRECOMPILE
104 #include <pcl/sample_consensus/impl/msac.hpp>
105 #endif
106 
107 #endif //#ifndef PCL_SAMPLE_CONSENSUS_MSAC_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::MEstimatorSampleConsensus
MEstimatorSampleConsensus represents an implementation of the MSAC (M-estimator SAmple Consensus) alg...
Definition: msac.h:57
pcl::MEstimatorSampleConsensus::Ptr
boost::shared_ptr< MEstimatorSampleConsensus > Ptr
Definition: msac.h:62
pcl::MEstimatorSampleConsensus::ConstPtr
boost::shared_ptr< const MEstimatorSampleConsensus > ConstPtr
Definition: msac.h:63
pcl::PointXYZRGB
A point structure representing Euclidean xyz coordinates, and the RGB color.
Definition: point_types.hpp:619
pcl::MEstimatorSampleConsensus::MEstimatorSampleConsensus
MEstimatorSampleConsensus(const SampleConsensusModelPtr &model, double threshold)
MSAC (M-estimator SAmple Consensus) main constructor.
Definition: msac.h:88
pcl::MEstimatorSampleConsensus::MEstimatorSampleConsensus
MEstimatorSampleConsensus(const SampleConsensusModelPtr &model)
MSAC (M-estimator SAmple Consensus) main constructor.
Definition: msac.h:77
pcl::MEstimatorSampleConsensus::computeModel
bool computeModel(int debug_verbosity_level=0)
Compute the actual model and find the inliers.
Definition: msac.hpp:48
pcl::SampleConsensus
SampleConsensus represents the base class.
Definition: sac.h:56
pcl::SampleConsensus< PointT >::max_iterations_
int max_iterations_
Maximum number of iterations before giving up.
Definition: sac.h:331