Visual Servoing Platform version 3.6.0
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vpRobust.h
1/*
2 * ViSP, open source Visual Servoing Platform software.
3 * Copyright (C) 2005 - 2023 by Inria. All rights reserved.
4 *
5 * This software is free software; you can redistribute it and/or modify
6 * it under the terms of the GNU General Public License as published by
7 * the Free Software Foundation; either version 2 of the License, or
8 * (at your option) any later version.
9 * See the file LICENSE.txt at the root directory of this source
10 * distribution for additional information about the GNU GPL.
11 *
12 * For using ViSP with software that can not be combined with the GNU
13 * GPL, please contact Inria about acquiring a ViSP Professional
14 * Edition License.
15 *
16 * See https://visp.inria.fr for more information.
17 *
18 * This software was developed at:
19 * Inria Rennes - Bretagne Atlantique
20 * Campus Universitaire de Beaulieu
21 * 35042 Rennes Cedex
22 * France
23 *
24 * If you have questions regarding the use of this file, please contact
25 * Inria at visp@inria.fr
26 *
27 * This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
28 * WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
29 *
30 * Description:
31 * M-Estimator and various influence function.
32 */
33
38#ifndef vpRobust_h
39#define vpRobust_h
40
41#include <visp3/core/vpColVector.h>
42#include <visp3/core/vpConfig.h>
43#include <visp3/core/vpMath.h>
44
82class VISP_EXPORT vpRobust
83{
84public:
86 typedef enum {
89 HUBER
90 } vpRobustEstimatorType;
91
92private:
94 vpColVector m_normres;
96 vpColVector m_sorted_normres;
98 vpColVector m_sorted_residues;
99
101 double m_mad_min;
103 double m_mad_prev;
104#if defined(VISP_BUILD_DEPRECATED_FUNCTIONS)
106 unsigned int m_iter;
107#endif
109 unsigned int m_size;
111 double m_mad;
112
113public:
114 vpRobust();
115 vpRobust(const vpRobust &other);
116
118 virtual ~vpRobust(){};
119
129 double getMedianAbsoluteDeviation() { return m_mad; };
130
137 double getMinMedianAbsoluteDeviation() { return m_mad_min; };
138
139 void MEstimator(const vpRobustEstimatorType method, const vpColVector &residues, vpColVector &weights);
140
141 vpRobust &operator=(const vpRobust &other);
142#if (VISP_CXX_STANDARD >= VISP_CXX_STANDARD_11)
143 vpRobust &operator=(const vpRobust &&other);
144#endif
145
155 inline void setMinMedianAbsoluteDeviation(double mad_min) { m_mad_min = mad_min; }
156
157#if defined(VISP_BUILD_DEPRECATED_FUNCTIONS)
162 vp_deprecated explicit vpRobust(unsigned int n_data);
164 void MEstimator(const vpRobustEstimatorType method, const vpColVector &residues, const vpColVector &all_residues,
165 vpColVector &weights);
170 vp_deprecated void setIteration(unsigned int iter) { m_iter = iter; }
179 vp_deprecated inline void setThreshold(double mad_min) { m_mad_min = mad_min; }
180 vp_deprecated vpColVector simultMEstimator(vpColVector &residues);
182#endif
183private:
185 void resize(unsigned int n_data);
186
187 //---------------------------------
188 // Partial derivative of loss function with respect to the residue
189 //---------------------------------
192
193 void psiTukey(double sigma, const vpColVector &x, vpColVector &w);
195 void psiCauchy(double sigma, const vpColVector &x, vpColVector &w);
197 void psiHuber(double sigma, const vpColVector &x, vpColVector &w);
199
200#if defined(VISP_BUILD_DEPRECATED_FUNCTIONS)
201 double computeNormalizedMedian(vpColVector &all_normres, const vpColVector &residues, const vpColVector &all_residues,
202 const vpColVector &weights);
204 double simultscale(const vpColVector &x);
206 double simult_chi_huber(double x);
207
208 //---------------------------------
209 // Constrained Partial derivative of loss function with respect to the scale
210 //---------------------------------
213
214 double constrainedChi(vpRobustEstimatorType method, double x);
216 double constrainedChiTukey(double x);
218 double constrainedChiCauchy(double x);
220 double constrainedChiHuber(double x);
222
223#if !defined(VISP_HAVE_FUNC_ERFC) && !defined(VISP_HAVE_FUNC_STD_ERFC)
224 //---------------------------------
225 // Mathematic functions used to calculate the Expectation
226 //---------------------------------
229 double erf(double x);
230 double gammp(double a, double x);
231 void gser(double *gamser, double a, double x, double *gln);
232 void gcf(double *gammcf, double a, double x, double *gln);
233 double gammln(double xx);
235#endif
236#endif
237
241 int partition(vpColVector &a, int l, int r);
243 double select(vpColVector &a, int l, int r, int k);
245};
246
247#endif
Implementation of column vector and the associated operations.
Contains an M-estimator and various influence function.
Definition vpRobust.h:83
@ TUKEY
Tukey influence function.
Definition vpRobust.h:87
@ CAUCHY
Cauchy influence function.
Definition vpRobust.h:88
void setMinMedianAbsoluteDeviation(double mad_min)
Definition vpRobust.h:155
vp_deprecated void setThreshold(double mad_min)
Definition vpRobust.h:179
double getMedianAbsoluteDeviation()
Definition vpRobust.h:129
double getMinMedianAbsoluteDeviation()
Definition vpRobust.h:137
virtual ~vpRobust()
Destructor.
Definition vpRobust.h:118
vp_deprecated void setIteration(unsigned int iter)
Definition vpRobust.h:170