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diff --git a/2.3-1/thirdparty/includes/OpenCV/opencv2/contrib/openfabmap.hpp b/2.3-1/thirdparty/includes/OpenCV/opencv2/contrib/openfabmap.hpp new file mode 100644 index 00000000..6b2834ed --- /dev/null +++ b/2.3-1/thirdparty/includes/OpenCV/opencv2/contrib/openfabmap.hpp @@ -0,0 +1,405 @@ +/*M/////////////////////////////////////////////////////////////////////////////////////// +// +// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. +// +// By downloading, copying, installing or using the software you agree to this license. +// If you do not agree to this license, do not download, install, +// copy or use the software. +// +// This file originates from the openFABMAP project: +// [http://code.google.com/p/openfabmap/] +// +// For published work which uses all or part of OpenFABMAP, please cite: +// [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6224843] +// +// Original Algorithm by Mark Cummins and Paul Newman: +// [http://ijr.sagepub.com/content/27/6/647.short] +// [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5613942] +// [http://ijr.sagepub.com/content/30/9/1100.abstract] +// +// License Agreement +// +// Copyright (C) 2012 Arren Glover [aj.glover@qut.edu.au] and +// Will Maddern [w.maddern@qut.edu.au], all rights reserved. +// +// +// Redistribution and use in source and binary forms, with or without modification, +// are permitted provided that the following conditions are met: +// +// * Redistribution's of source code must retain the above copyright notice, +// this list of conditions and the following disclaimer. +// +// * Redistribution's in binary form must reproduce the above copyright notice, +// this list of conditions and the following disclaimer in the documentation +// and/or other materials provided with the distribution. +// +// * The name of the copyright holders may not be used to endorse or promote products +// derived from this software without specific prior written permission. +// +// This software is provided by the copyright holders and contributors "as is" and +// any express or implied warranties, including, but not limited to, the implied +// warranties of merchantability and fitness for a particular purpose are disclaimed. +// In no event shall the Intel Corporation or contributors be liable for any direct, +// indirect, incidental, special, exemplary, or consequential damages +// (including, but not limited to, procurement of substitute goods or services; +// loss of use, data, or profits; or business interruption) however caused +// and on any theory of liability, whether in contract, strict liability, +// or tort (including negligence or otherwise) arising in any way out of +// the use of this software, even if advised of the possibility of such damage. +// +//M*/ + +#ifndef __OPENCV_OPENFABMAP_H_ +#define __OPENCV_OPENFABMAP_H_ + +#include "opencv2/core/core.hpp" +#include "opencv2/features2d/features2d.hpp" + +#include <vector> +#include <list> +#include <map> +#include <set> +#include <valarray> + +namespace cv { + +namespace of2 { + +using std::list; +using std::map; +using std::multiset; + +/* + Return data format of a FABMAP compare call +*/ +struct CV_EXPORTS IMatch { + + IMatch() : + queryIdx(-1), imgIdx(-1), likelihood(-DBL_MAX), match(-DBL_MAX) { + } + IMatch(int _queryIdx, int _imgIdx, double _likelihood, double _match) : + queryIdx(_queryIdx), imgIdx(_imgIdx), likelihood(_likelihood), match( + _match) { + } + + int queryIdx; //query index + int imgIdx; //test index + + double likelihood; //raw loglikelihood + double match; //normalised probability + + bool operator<(const IMatch& m) const { + return match < m.match; + } + +}; + +/* + Base FabMap class. Each FabMap method inherits from this class. +*/ +class CV_EXPORTS FabMap { +public: + + //FabMap options + enum { + MEAN_FIELD = 1, + SAMPLED = 2, + NAIVE_BAYES = 4, + CHOW_LIU = 8, + MOTION_MODEL = 16 + }; + + FabMap(const Mat& clTree, double PzGe, double PzGNe, int flags, + int numSamples = 0); + virtual ~FabMap(); + + //methods to add training data for sampling method + virtual void addTraining(const Mat& queryImgDescriptor); + virtual void addTraining(const vector<Mat>& queryImgDescriptors); + + //methods to add to the test data + virtual void add(const Mat& queryImgDescriptor); + virtual void add(const vector<Mat>& queryImgDescriptors); + + //accessors + const vector<Mat>& getTrainingImgDescriptors() const; + const vector<Mat>& getTestImgDescriptors() const; + + //Main FabMap image comparison + void compare(const Mat& queryImgDescriptor, + vector<IMatch>& matches, bool addQuery = false, + const Mat& mask = Mat()); + void compare(const Mat& queryImgDescriptor, + const Mat& testImgDescriptors, vector<IMatch>& matches, + const Mat& mask = Mat()); + void compare(const Mat& queryImgDescriptor, + const vector<Mat>& testImgDescriptors, + vector<IMatch>& matches, const Mat& mask = Mat()); + void compare(const vector<Mat>& queryImgDescriptors, vector< + IMatch>& matches, bool addQuery = false, const Mat& mask = + Mat()); + void compare(const vector<Mat>& queryImgDescriptors, + const vector<Mat>& testImgDescriptors, + vector<IMatch>& matches, const Mat& mask = Mat()); + +protected: + + void compareImgDescriptor(const Mat& queryImgDescriptor, + int queryIndex, const vector<Mat>& testImgDescriptors, + vector<IMatch>& matches); + + void addImgDescriptor(const Mat& queryImgDescriptor); + + //the getLikelihoods method is overwritten for each different FabMap + //method. + virtual void getLikelihoods(const Mat& queryImgDescriptor, + const vector<Mat>& testImgDescriptors, + vector<IMatch>& matches); + virtual double getNewPlaceLikelihood(const Mat& queryImgDescriptor); + + //turn likelihoods into probabilities (also add in motion model if used) + void normaliseDistribution(vector<IMatch>& matches); + + //Chow-Liu Tree + int pq(int q); + double Pzq(int q, bool zq); + double PzqGzpq(int q, bool zq, bool zpq); + + //FAB-MAP Core + double PzqGeq(bool zq, bool eq); + double PeqGL(int q, bool Lzq, bool eq); + double PzqGL(int q, bool zq, bool zpq, bool Lzq); + double PzqGzpqL(int q, bool zq, bool zpq, bool Lzq); + double (FabMap::*PzGL)(int q, bool zq, bool zpq, bool Lzq); + + //data + Mat clTree; + vector<Mat> trainingImgDescriptors; + vector<Mat> testImgDescriptors; + vector<IMatch> priorMatches; + + //parameters + double PzGe; + double PzGNe; + double Pnew; + + double mBias; + double sFactor; + + int flags; + int numSamples; + +}; + +/* + The original FAB-MAP algorithm, developed based on: + http://ijr.sagepub.com/content/27/6/647.short +*/ +class CV_EXPORTS FabMap1: public FabMap { +public: + FabMap1(const Mat& clTree, double PzGe, double PzGNe, int flags, + int numSamples = 0); + virtual ~FabMap1(); +protected: + + //FabMap1 implementation of likelihood comparison + void getLikelihoods(const Mat& queryImgDescriptor, const vector< + Mat>& testImgDescriptors, vector<IMatch>& matches); +}; + +/* + A computationally faster version of the original FAB-MAP algorithm. A look- + up-table is used to precompute many of the reoccuring calculations +*/ +class CV_EXPORTS FabMapLUT: public FabMap { +public: + FabMapLUT(const Mat& clTree, double PzGe, double PzGNe, + int flags, int numSamples = 0, int precision = 6); + virtual ~FabMapLUT(); +protected: + + //FabMap look-up-table implementation of the likelihood comparison + void getLikelihoods(const Mat& queryImgDescriptor, const vector< + Mat>& testImgDescriptors, vector<IMatch>& matches); + + //precomputed data + int (*table)[8]; + + //data precision + int precision; +}; + +/* + The Accelerated FAB-MAP algorithm, developed based on: + http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5613942 +*/ +class CV_EXPORTS FabMapFBO: public FabMap { +public: + FabMapFBO(const Mat& clTree, double PzGe, double PzGNe, int flags, + int numSamples = 0, double rejectionThreshold = 1e-8, double PsGd = + 1e-8, int bisectionStart = 512, int bisectionIts = 9); + virtual ~FabMapFBO(); + +protected: + + //FabMap Fast Bail-out implementation of the likelihood comparison + void getLikelihoods(const Mat& queryImgDescriptor, const vector< + Mat>& testImgDescriptors, vector<IMatch>& matches); + + //stucture used to determine word comparison order + struct WordStats { + WordStats() : + q(0), info(0), V(0), M(0) { + } + + WordStats(int _q, double _info) : + q(_q), info(_info), V(0), M(0) { + } + + int q; + double info; + mutable double V; + mutable double M; + + bool operator<(const WordStats& w) const { + return info < w.info; + } + + }; + + //private fast bail-out necessary functions + void setWordStatistics(const Mat& queryImgDescriptor, multiset<WordStats>& wordData); + double limitbisection(double v, double m); + double bennettInequality(double v, double m, double delta); + static bool compInfo(const WordStats& first, const WordStats& second); + + //parameters + double PsGd; + double rejectionThreshold; + int bisectionStart; + int bisectionIts; +}; + +/* + The FAB-MAP2.0 algorithm, developed based on: + http://ijr.sagepub.com/content/30/9/1100.abstract +*/ +class CV_EXPORTS FabMap2: public FabMap { +public: + + FabMap2(const Mat& clTree, double PzGe, double PzGNe, int flags); + virtual ~FabMap2(); + + //FabMap2 builds the inverted index and requires an additional training/test + //add function + void addTraining(const Mat& queryImgDescriptors) { + FabMap::addTraining(queryImgDescriptors); + } + void addTraining(const vector<Mat>& queryImgDescriptors); + + void add(const Mat& queryImgDescriptors) { + FabMap::add(queryImgDescriptors); + } + void add(const vector<Mat>& queryImgDescriptors); + +protected: + + //FabMap2 implementation of the likelihood comparison + void getLikelihoods(const Mat& queryImgDescriptor, const vector< + Mat>& testImgDescriptors, vector<IMatch>& matches); + double getNewPlaceLikelihood(const Mat& queryImgDescriptor); + + //the likelihood function using the inverted index + void getIndexLikelihoods(const Mat& queryImgDescriptor, vector< + double>& defaults, map<int, vector<int> >& invertedMap, + vector<IMatch>& matches); + void addToIndex(const Mat& queryImgDescriptor, + vector<double>& defaults, + map<int, vector<int> >& invertedMap); + + //data + vector<double> d1, d2, d3, d4; + vector<vector<int> > children; + + // TODO: inverted map a vector? + + vector<double> trainingDefaults; + map<int, vector<int> > trainingInvertedMap; + + vector<double> testDefaults; + map<int, vector<int> > testInvertedMap; + +}; +/* + A Chow-Liu tree is required by FAB-MAP. The Chow-Liu tree provides an + estimate of the full distribution of visual words using a minimum spanning + tree. The tree is generated through training data. +*/ +class CV_EXPORTS ChowLiuTree { +public: + ChowLiuTree(); + virtual ~ChowLiuTree(); + + //add data to the chow-liu tree before calling make + void add(const Mat& imgDescriptor); + void add(const vector<Mat>& imgDescriptors); + + const vector<Mat>& getImgDescriptors() const; + + Mat make(double infoThreshold = 0.0); + +private: + vector<Mat> imgDescriptors; + Mat mergedImgDescriptors; + + typedef struct info { + float score; + short word1; + short word2; + } info; + + //probabilities extracted from mergedImgDescriptors + double P(int a, bool za); + double JP(int a, bool za, int b, bool zb); //a & b + double CP(int a, bool za, int b, bool zb); // a | b + + //calculating mutual information of all edges + void createBaseEdges(list<info>& edges, double infoThreshold); + double calcMutInfo(int word1, int word2); + static bool sortInfoScores(const info& first, const info& second); + + //selecting minimum spanning egdges with maximum information + bool reduceEdgesToMinSpan(list<info>& edges); + + //building the tree sctructure + Mat buildTree(int root_word, list<info> &edges); + void recAddToTree(Mat &cltree, int q, int pq, + list<info> &remaining_edges); + vector<int> extractChildren(list<info> &remaining_edges, int q); + +}; + +/* + A custom vocabulary training method based on: + http://www.springerlink.com/content/d1h6j8x552532003/ +*/ +class CV_EXPORTS BOWMSCTrainer: public BOWTrainer { +public: + BOWMSCTrainer(double clusterSize = 0.4); + virtual ~BOWMSCTrainer(); + + // Returns trained vocabulary (i.e. cluster centers). + virtual Mat cluster() const; + virtual Mat cluster(const Mat& descriptors) const; + +protected: + + double clusterSize; + +}; + +} + +} + +#endif /* OPENFABMAP_H_ */ |