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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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//
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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, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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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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//
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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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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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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_GPUBGSEGM_HPP__
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#define __OPENCV_GPUBGSEGM_HPP__
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#ifndef __cplusplus
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# error gpubgsegm.hpp header must be compiled as C++
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#endif
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#include "opencv2/core/gpu.hpp"
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#include "opencv2/video/background_segm.hpp"
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namespace cv { namespace gpu {
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////////////////////////////////////////////////////
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// MOG
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class CV_EXPORTS BackgroundSubtractorMOG : public cv::BackgroundSubtractorMOG
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{
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public:
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using cv::BackgroundSubtractorMOG::apply;
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using cv::BackgroundSubtractorMOG::getBackgroundImage;
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virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;
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virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0;
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};
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CV_EXPORTS Ptr<gpu::BackgroundSubtractorMOG>
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createBackgroundSubtractorMOG(int history = 200, int nmixtures = 5,
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double backgroundRatio = 0.7, double noiseSigma = 0);
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////////////////////////////////////////////////////
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// MOG2
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class CV_EXPORTS BackgroundSubtractorMOG2 : public cv::BackgroundSubtractorMOG2
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{
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public:
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using cv::BackgroundSubtractorMOG2::apply;
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using cv::BackgroundSubtractorMOG2::getBackgroundImage;
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virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;
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virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0;
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};
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CV_EXPORTS Ptr<gpu::BackgroundSubtractorMOG2>
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createBackgroundSubtractorMOG2(int history = 500, double varThreshold = 16,
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bool detectShadows = true);
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////////////////////////////////////////////////////
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// GMG
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class CV_EXPORTS BackgroundSubtractorGMG : public cv::BackgroundSubtractorGMG
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{
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public:
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using cv::BackgroundSubtractorGMG::apply;
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virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;
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};
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CV_EXPORTS Ptr<gpu::BackgroundSubtractorGMG>
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createBackgroundSubtractorGMG(int initializationFrames = 120, double decisionThreshold = 0.8);
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////////////////////////////////////////////////////
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// FGD
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/**
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* Foreground Object Detection from Videos Containing Complex Background.
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* Liyuan Li, Weimin Huang, Irene Y.H. Gu, and Qi Tian.
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* ACM MM2003 9p
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*/
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class CV_EXPORTS BackgroundSubtractorFGD : public cv::BackgroundSubtractor
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{
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public:
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virtual void getForegroundRegions(OutputArrayOfArrays foreground_regions) = 0;
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};
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struct CV_EXPORTS FGDParams
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{
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int Lc; // Quantized levels per 'color' component. Power of two, typically 32, 64 or 128.
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int N1c; // Number of color vectors used to model normal background color variation at a given pixel.
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int N2c; // Number of color vectors retained at given pixel. Must be > N1c, typically ~ 5/3 of N1c.
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// Used to allow the first N1c vectors to adapt over time to changing background.
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int Lcc; // Quantized levels per 'color co-occurrence' component. Power of two, typically 16, 32 or 64.
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int N1cc; // Number of color co-occurrence vectors used to model normal background color variation at a given pixel.
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int N2cc; // Number of color co-occurrence vectors retained at given pixel. Must be > N1cc, typically ~ 5/3 of N1cc.
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// Used to allow the first N1cc vectors to adapt over time to changing background.
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bool is_obj_without_holes; // If TRUE we ignore holes within foreground blobs. Defaults to TRUE.
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int perform_morphing; // Number of erode-dilate-erode foreground-blob cleanup iterations.
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// These erase one-pixel junk blobs and merge almost-touching blobs. Default value is 1.
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float alpha1; // How quickly we forget old background pixel values seen. Typically set to 0.1.
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float alpha2; // "Controls speed of feature learning". Depends on T. Typical value circa 0.005.
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float alpha3; // Alternate to alpha2, used (e.g.) for quicker initial convergence. Typical value 0.1.
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float delta; // Affects color and color co-occurrence quantization, typically set to 2.
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float T; // A percentage value which determines when new features can be recognized as new background. (Typically 0.9).
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float minArea; // Discard foreground blobs whose bounding box is smaller than this threshold.
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// default Params
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FGDParams();
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};
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CV_EXPORTS Ptr<gpu::BackgroundSubtractorFGD>
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createBackgroundSubtractorFGD(const FGDParams& params = FGDParams());
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}} // namespace cv { namespace gpu {
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#endif /* __OPENCV_GPUBGSEGM_HPP__ */
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