OpenGV
A library for solving calibrated central and non-central geometric vision problems
 
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Ransac.hpp
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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
38#ifndef OPENGV_SAC_RANSAC_HPP_
39#define OPENGV_SAC_RANSAC_HPP_
40
41#include <vector>
43#include <cstdio>
44
48namespace opengv
49{
53namespace sac
54{
55
59template<typename PROBLEM_T>
60class Ransac : public SampleConsensus<PROBLEM_T>
61{
62public:
64 typedef PROBLEM_T problem_t;
66 typedef typename problem_t::model_t model_t;
67
76
81 int maxIterations = 1000,
82 double threshold = 1.0,
83 double probability = 0.99 );
87 virtual ~Ransac();
88
92 bool computeModel( int debug_verbosity_level = 0 );
93};
94
95} // namespace sac
96} // namespace opengv
97
98#include "implementation/Ransac.hpp"
99
100#endif /* OPENGV_SAC_RANSAC_HPP_ */
This is a base class for sample consensus methods such as Ransac. Derivatives call the three basic fu...
Definition Ransac.hpp:61
bool computeModel(int debug_verbosity_level=0)
Fit the model.
virtual ~Ransac()
Destructor.
Ransac(int maxIterations=1000, double threshold=1.0, double probability=0.99)
Constructor.
PROBLEM_T problem_t
Definition Ransac.hpp:64
problem_t::model_t model_t
Definition Ransac.hpp:66
Definition SampleConsensus.hpp:62
std::vector< int > model_
Definition SampleConsensus.hpp:109
double probability_
Definition SampleConsensus.hpp:105
int max_iterations_
Definition SampleConsensus.hpp:99
double threshold_
Definition SampleConsensus.hpp:103
model_t model_coefficients_
Definition SampleConsensus.hpp:107
std::vector< int > inliers_
Definition SampleConsensus.hpp:111
std::shared_ptr< PROBLEM_T > sac_model_
Definition SampleConsensus.hpp:113
int iterations_
Definition SampleConsensus.hpp:101
The namespace of this library.
Definition AbsoluteAdapterBase.hpp:48