mirror of https://github.com/opencv/opencv.git
Andrey Kamaev
12 years ago
parent
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commit
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * The name of the copyright holders may not be used to endorse or promote products
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// This software is provided by the copyright holders and contributors "as is" and
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_CONTRIB_COMPAT_HPP__ |
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#define __OPENCV_CONTRIB_COMPAT_HPP__ |
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#include "opencv2/core/core_c.h" |
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#ifdef __cplusplus |
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/****************************************************************************************\
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* Adaptive Skin Detector * |
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\****************************************************************************************/ |
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class CV_EXPORTS CvAdaptiveSkinDetector |
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{ |
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private: |
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enum { |
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GSD_HUE_LT = 3, |
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GSD_HUE_UT = 33, |
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GSD_INTENSITY_LT = 15, |
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GSD_INTENSITY_UT = 250 |
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}; |
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class CV_EXPORTS Histogram |
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{ |
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private: |
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enum { |
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HistogramSize = (GSD_HUE_UT - GSD_HUE_LT + 1) |
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}; |
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protected: |
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int findCoverageIndex(double surfaceToCover, int defaultValue = 0); |
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public: |
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CvHistogram *fHistogram; |
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Histogram(); |
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virtual ~Histogram(); |
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void findCurveThresholds(int &x1, int &x2, double percent = 0.05); |
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void mergeWith(Histogram *source, double weight); |
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}; |
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int nStartCounter, nFrameCount, nSkinHueLowerBound, nSkinHueUpperBound, nMorphingMethod, nSamplingDivider; |
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double fHistogramMergeFactor, fHuePercentCovered; |
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Histogram histogramHueMotion, skinHueHistogram; |
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IplImage *imgHueFrame, *imgSaturationFrame, *imgLastGrayFrame, *imgMotionFrame, *imgFilteredFrame; |
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IplImage *imgShrinked, *imgTemp, *imgGrayFrame, *imgHSVFrame; |
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protected: |
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void initData(IplImage *src, int widthDivider, int heightDivider); |
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void adaptiveFilter(); |
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public: |
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enum { |
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MORPHING_METHOD_NONE = 0, |
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MORPHING_METHOD_ERODE = 1, |
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MORPHING_METHOD_ERODE_ERODE = 2, |
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MORPHING_METHOD_ERODE_DILATE = 3 |
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}; |
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CvAdaptiveSkinDetector(int samplingDivider = 1, int morphingMethod = MORPHING_METHOD_NONE); |
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virtual ~CvAdaptiveSkinDetector(); |
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virtual void process(IplImage *inputBGRImage, IplImage *outputHueMask); |
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}; |
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/****************************************************************************************\
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* Fuzzy MeanShift Tracker * |
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\****************************************************************************************/ |
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class CV_EXPORTS CvFuzzyPoint { |
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public: |
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double x, y, value; |
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CvFuzzyPoint(double _x, double _y); |
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}; |
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class CV_EXPORTS CvFuzzyCurve { |
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private: |
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std::vector<CvFuzzyPoint> points; |
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double value, centre; |
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bool between(double x, double x1, double x2); |
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public: |
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CvFuzzyCurve(); |
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~CvFuzzyCurve(); |
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void setCentre(double _centre); |
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double getCentre(); |
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void clear(); |
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void addPoint(double x, double y); |
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double calcValue(double param); |
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double getValue(); |
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void setValue(double _value); |
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}; |
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class CV_EXPORTS CvFuzzyFunction { |
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public: |
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std::vector<CvFuzzyCurve> curves; |
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CvFuzzyFunction(); |
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~CvFuzzyFunction(); |
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void addCurve(CvFuzzyCurve *curve, double value = 0); |
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void resetValues(); |
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double calcValue(); |
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CvFuzzyCurve *newCurve(); |
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}; |
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class CV_EXPORTS CvFuzzyRule { |
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private: |
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CvFuzzyCurve *fuzzyInput1, *fuzzyInput2; |
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CvFuzzyCurve *fuzzyOutput; |
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public: |
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CvFuzzyRule(); |
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~CvFuzzyRule(); |
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void setRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1); |
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double calcValue(double param1, double param2); |
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CvFuzzyCurve *getOutputCurve(); |
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}; |
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class CV_EXPORTS CvFuzzyController { |
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private: |
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std::vector<CvFuzzyRule*> rules; |
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public: |
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CvFuzzyController(); |
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~CvFuzzyController(); |
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void addRule(CvFuzzyCurve *c1, CvFuzzyCurve *c2, CvFuzzyCurve *o1); |
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double calcOutput(double param1, double param2); |
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}; |
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class CV_EXPORTS CvFuzzyMeanShiftTracker |
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{ |
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private: |
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class FuzzyResizer |
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{ |
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private: |
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CvFuzzyFunction iInput, iOutput; |
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CvFuzzyController fuzzyController; |
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public: |
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FuzzyResizer(); |
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int calcOutput(double edgeDensity, double density); |
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}; |
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class SearchWindow |
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{ |
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public: |
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FuzzyResizer *fuzzyResizer; |
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int x, y; |
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int width, height, maxWidth, maxHeight, ellipseHeight, ellipseWidth; |
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int ldx, ldy, ldw, ldh, numShifts, numIters; |
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int xGc, yGc; |
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long m00, m01, m10, m11, m02, m20; |
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double ellipseAngle; |
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double density; |
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unsigned int depthLow, depthHigh; |
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int verticalEdgeLeft, verticalEdgeRight, horizontalEdgeTop, horizontalEdgeBottom; |
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SearchWindow(); |
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~SearchWindow(); |
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void setSize(int _x, int _y, int _width, int _height); |
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void initDepthValues(IplImage *maskImage, IplImage *depthMap); |
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bool shift(); |
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void extractInfo(IplImage *maskImage, IplImage *depthMap, bool initDepth); |
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void getResizeAttribsEdgeDensityLinear(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh); |
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void getResizeAttribsInnerDensity(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh); |
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void getResizeAttribsEdgeDensityFuzzy(int &resizeDx, int &resizeDy, int &resizeDw, int &resizeDh); |
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bool meanShift(IplImage *maskImage, IplImage *depthMap, int maxIteration, bool initDepth); |
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}; |
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public: |
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enum TrackingState |
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{ |
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tsNone = 0, |
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tsSearching = 1, |
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tsTracking = 2, |
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tsSetWindow = 3, |
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tsDisabled = 10 |
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}; |
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enum ResizeMethod { |
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rmEdgeDensityLinear = 0, |
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rmEdgeDensityFuzzy = 1, |
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rmInnerDensity = 2 |
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}; |
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enum { |
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MinKernelMass = 1000 |
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}; |
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SearchWindow kernel; |
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int searchMode; |
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private: |
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enum
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{ |
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MaxMeanShiftIteration = 5, |
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MaxSetSizeIteration = 5 |
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}; |
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void findOptimumSearchWindow(SearchWindow &searchWindow, IplImage *maskImage, IplImage *depthMap, int maxIteration, int resizeMethod, bool initDepth); |
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public: |
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CvFuzzyMeanShiftTracker(); |
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~CvFuzzyMeanShiftTracker(); |
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void track(IplImage *maskImage, IplImage *depthMap, int resizeMethod, bool resetSearch, int minKernelMass = MinKernelMass); |
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}; |
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namespace cv |
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{ |
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typedef bool (*BundleAdjustCallback)(int iteration, double norm_error, void* user_data); |
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class CV_EXPORTS LevMarqSparse { |
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public: |
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LevMarqSparse(); |
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LevMarqSparse(int npoints, // number of points
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int ncameras, // number of cameras
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int nPointParams, // number of params per one point (3 in case of 3D points)
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int nCameraParams, // number of parameters per one camera
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int nErrParams, // number of parameters in measurement vector
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// for 1 point at one camera (2 in case of 2D projections)
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Mat& visibility, // visibility matrix. rows correspond to points, columns correspond to cameras
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// 1 - point is visible for the camera, 0 - invisible
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Mat& P0, // starting vector of parameters, first cameras then points
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Mat& X, // measurements, in order of visibility. non visible cases are skipped
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TermCriteria criteria, // termination criteria
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// callback for estimation of Jacobian matrices
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void (*fjac)(int i, int j, Mat& point_params, |
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Mat& cam_params, Mat& A, Mat& B, void* data), |
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// callback for estimation of backprojection errors
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void (*func)(int i, int j, Mat& point_params, |
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Mat& cam_params, Mat& estim, void* data), |
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void* data, // user-specific data passed to the callbacks
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BundleAdjustCallback cb, void* user_data |
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); |
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virtual ~LevMarqSparse(); |
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virtual void run( int npoints, // number of points
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int ncameras, // number of cameras
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int nPointParams, // number of params per one point (3 in case of 3D points)
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int nCameraParams, // number of parameters per one camera
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int nErrParams, // number of parameters in measurement vector
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// for 1 point at one camera (2 in case of 2D projections)
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Mat& visibility, // visibility matrix. rows correspond to points, columns correspond to cameras
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// 1 - point is visible for the camera, 0 - invisible
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Mat& P0, // starting vector of parameters, first cameras then points
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Mat& X, // measurements, in order of visibility. non visible cases are skipped
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TermCriteria criteria, // termination criteria
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// callback for estimation of Jacobian matrices
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void (CV_CDECL * fjac)(int i, int j, Mat& point_params, |
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Mat& cam_params, Mat& A, Mat& B, void* data), |
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// callback for estimation of backprojection errors
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void (CV_CDECL * func)(int i, int j, Mat& point_params, |
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Mat& cam_params, Mat& estim, void* data), |
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void* data // user-specific data passed to the callbacks
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); |
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virtual void clear(); |
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// useful function to do simple bundle adjustment tasks
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static void bundleAdjust(std::vector<Point3d>& points, // positions of points in global coordinate system (input and output)
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const std::vector<std::vector<Point2d> >& imagePoints, // projections of 3d points for every camera
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const std::vector<std::vector<int> >& visibility, // visibility of 3d points for every camera
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std::vector<Mat>& cameraMatrix, // intrinsic matrices of all cameras (input and output)
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std::vector<Mat>& R, // rotation matrices of all cameras (input and output)
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std::vector<Mat>& T, // translation vector of all cameras (input and output)
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std::vector<Mat>& distCoeffs, // distortion coefficients of all cameras (input and output)
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const TermCriteria& criteria= |
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TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, DBL_EPSILON), |
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BundleAdjustCallback cb = 0, void* user_data = 0); |
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public: |
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virtual void optimize(CvMat &_vis); //main function that runs minimization
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//iteratively asks for measurement for visible camera-point pairs
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void ask_for_proj(CvMat &_vis,bool once=false); |
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//iteratively asks for Jacobians for every camera_point pair
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void ask_for_projac(CvMat &_vis); |
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CvMat* err; //error X-hX
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double prevErrNorm, errNorm; |
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double lambda; |
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CvTermCriteria criteria; |
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int iters; |
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CvMat** U; //size of array is equal to number of cameras
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CvMat** V; //size of array is equal to number of points
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CvMat** inv_V_star; //inverse of V*
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CvMat** A; |
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CvMat** B; |
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CvMat** W; |
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CvMat* X; //measurement
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CvMat* hX; //current measurement extimation given new parameter vector
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CvMat* prevP; //current already accepted parameter.
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CvMat* P; // parameters used to evaluate function with new params
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// this parameters may be rejected
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CvMat* deltaP; //computed increase of parameters (result of normal system solution )
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CvMat** ea; // sum_i AijT * e_ij , used as right part of normal equation
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// length of array is j = number of cameras
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CvMat** eb; // sum_j BijT * e_ij , used as right part of normal equation
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// length of array is i = number of points
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CvMat** Yj; //length of array is i = num_points
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CvMat* S; //big matrix of block Sjk , each block has size num_cam_params x num_cam_params
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CvMat* JtJ_diag; //diagonal of JtJ, used to backup diagonal elements before augmentation
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CvMat* Vis_index; // matrix which element is index of measurement for point i and camera j
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int num_cams; |
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int num_points; |
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int num_err_param; |
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int num_cam_param; |
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int num_point_param; |
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//target function and jacobian pointers, which needs to be initialized
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void (*fjac)(int i, int j, Mat& point_params, Mat& cam_params, Mat& A, Mat& B, void* data); |
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void (*func)(int i, int j, Mat& point_params, Mat& cam_params, Mat& estim, void* data); |
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void* data; |
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BundleAdjustCallback cb; |
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void* user_data; |
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}; |
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} // cv
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#endif /* __cplusplus */ |
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#endif /* __OPENCV_CONTRIB_COMPAT_HPP__ */ |
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