/*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. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // 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_GPUBGSEGM_HPP__ #define __OPENCV_GPUBGSEGM_HPP__ #ifndef __cplusplus # error gpubgsegm.hpp header must be compiled as C++ #endif #include "opencv2/core/gpu.hpp" #include "opencv2/video/background_segm.hpp" namespace cv { namespace gpu { //////////////////////////////////////////////////// // MOG class CV_EXPORTS BackgroundSubtractorMOG : public cv::BackgroundSubtractorMOG { public: using cv::BackgroundSubtractorMOG::apply; using cv::BackgroundSubtractorMOG::getBackgroundImage; virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0; virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0; }; CV_EXPORTS Ptr createBackgroundSubtractorMOG(int history = 200, int nmixtures = 5, double backgroundRatio = 0.7, double noiseSigma = 0); //////////////////////////////////////////////////// // MOG2 class CV_EXPORTS BackgroundSubtractorMOG2 : public cv::BackgroundSubtractorMOG2 { public: using cv::BackgroundSubtractorMOG2::apply; using cv::BackgroundSubtractorMOG2::getBackgroundImage; virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0; virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0; }; CV_EXPORTS Ptr createBackgroundSubtractorMOG2(int history = 500, double varThreshold = 16, bool detectShadows = true); //////////////////////////////////////////////////// // GMG class CV_EXPORTS BackgroundSubtractorGMG : public cv::BackgroundSubtractorGMG { public: using cv::BackgroundSubtractorGMG::apply; virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0; }; CV_EXPORTS Ptr createBackgroundSubtractorGMG(int initializationFrames = 120, double decisionThreshold = 0.8); //////////////////////////////////////////////////// // FGD /** * Foreground Object Detection from Videos Containing Complex Background. * Liyuan Li, Weimin Huang, Irene Y.H. Gu, and Qi Tian. * ACM MM2003 9p */ class CV_EXPORTS BackgroundSubtractorFGD : public cv::BackgroundSubtractor { public: virtual void getForegroundRegions(OutputArrayOfArrays foreground_regions) = 0; }; struct CV_EXPORTS FGDParams { int Lc; // Quantized levels per 'color' component. Power of two, typically 32, 64 or 128. int N1c; // Number of color vectors used to model normal background color variation at a given pixel. int N2c; // Number of color vectors retained at given pixel. Must be > N1c, typically ~ 5/3 of N1c. // Used to allow the first N1c vectors to adapt over time to changing background. int Lcc; // Quantized levels per 'color co-occurrence' component. Power of two, typically 16, 32 or 64. int N1cc; // Number of color co-occurrence vectors used to model normal background color variation at a given pixel. int N2cc; // Number of color co-occurrence vectors retained at given pixel. Must be > N1cc, typically ~ 5/3 of N1cc. // Used to allow the first N1cc vectors to adapt over time to changing background. bool is_obj_without_holes; // If TRUE we ignore holes within foreground blobs. Defaults to TRUE. int perform_morphing; // Number of erode-dilate-erode foreground-blob cleanup iterations. // These erase one-pixel junk blobs and merge almost-touching blobs. Default value is 1. float alpha1; // How quickly we forget old background pixel values seen. Typically set to 0.1. float alpha2; // "Controls speed of feature learning". Depends on T. Typical value circa 0.005. float alpha3; // Alternate to alpha2, used (e.g.) for quicker initial convergence. Typical value 0.1. float delta; // Affects color and color co-occurrence quantization, typically set to 2. float T; // A percentage value which determines when new features can be recognized as new background. (Typically 0.9). float minArea; // Discard foreground blobs whose bounding box is smaller than this threshold. // default Params FGDParams(); }; CV_EXPORTS Ptr createBackgroundSubtractorFGD(const FGDParams& params = FGDParams()); }} // namespace cv { namespace gpu { #endif /* __OPENCV_GPUBGSEGM_HPP__ */