1 /******************************************************************************
2  * Authors:  Laurent Kneip & Paul Furgale                                     *
3  * Contact:  kneip.laurent@gmail.com                                          *
4  * License:  Copyright (c) 2013 Laurent Kneip, ANU. All rights reserved.      *
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30 
31 //Note: has been derived from ROS
32 
33 /**
34  * \file SampleConsensus.hpp
35  * \brief This is a base class for sample consensus methods such as Ransac.
36  *        Derivatives call the three basic functions of a sample-consensus
37  *        problem (sample drawing, computation of a hypothesis, and verification
38  *        of a hypothesis).
39  */
40 
41 #ifndef OPENGV_SAC_SAMPLECONSENSUS_HPP_
42 #define OPENGV_SAC_SAMPLECONSENSUS_HPP_
43 
44 #include <memory>
45 
46 /**
47  * \brief The namespace of this library.
48  */
49 namespace opengv
50 {
51 /**
52  * \brief The namespace for the sample consensus methods.
53  */
54 namespace sac
55 {
56 
57 /**
58  * Super-class for sample consensus methods, such as Ransac.
59  */
60 template<typename PROBLEM_T>
61 class SampleConsensus
62 {
63 public:
64   EIGEN_MAKE_ALIGNED_OPERATOR_NEW
65   /** A child of SampleConsensusProblem */
66   typedef PROBLEM_T problem_t;
67   /** The model we trying to fit */
68   typedef typename problem_t::model_t model_t;
69 
70   /**
71    * \brief Constructor.
72    * \param[in] maxIterations The maximum number of hypothesis generations
73    * \param[in] threshold Some threshold value for classifying samples as
74    *                      an inlier or an outlier.
75    * \param[in] probability The probability of being able to draw at least one
76    *                        sample that is free of outliers (see [15])
77    */
78   SampleConsensus(
79       int maxIterations = 1000,
80       double threshold = 1.0,
81       double probability = 0.99 );
82   /**
83    * \brief Destructor
84    */
85   virtual ~SampleConsensus();
86 
87   /**
88    * \brief Fit the model to the data.
89    * \param[in] debug_verbosity_level Sets the verbosity level.
90    * \return bool True if success.
91    */
92   virtual bool computeModel(
93       int debug_verbosity_level = 0 ) = 0;
94 
95   // \todo accessors
96   //private:
97 
98   /** the maximum number of iterations */
99   int max_iterations_;
100   /** the current number of iterations */
101   int iterations_;
102   /** the threshold for classifying inliers */
103   double threshold_;
104   /** the current probability (defines remaining iterations) */
105   double probability_;
106   /** the currently best model coefficients */
107   model_t model_coefficients_;
108   /** the indices for the currently best hypothesis */
109   std::vector<int> model_;
110   /** the indices of the samples that have been clasified as inliers */
111   std::vector<int> inliers_;
112   /** the sample-consensus problem we are trying to solve */
113   std::shared_ptr<PROBLEM_T> sac_model_;
114 };
115 
116 } // namespace sac
117 } // namespace opengv
118 
119 #include "implementation/SampleConsensus.hpp"
120 
121 #endif /* OPENGV_SAC_SAMPLECONSENSUS_HPP_ */
122