/*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_CUDABGSEGM_HPP #define OPENCV_CUDABGSEGM_HPP #ifndef __cplusplus # error cudabgsegm.hpp header must be compiled as C++ #endif #include "opencv2/core/cuda.hpp" #include "opencv2/video/background_segm.hpp" /** @addtogroup cuda @{ @defgroup cudabgsegm Background Segmentation @} */ namespace cv { namespace cuda { //! @addtogroup cudabgsegm //! @{ //////////////////////////////////////////////////// // MOG /** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm. The class discriminates between foreground and background pixels by building and maintaining a model of the background. Any pixel which does not fit this model is then deemed to be foreground. The class implements algorithm described in @cite MOG2001 . @sa BackgroundSubtractorMOG @note - An example on gaussian mixture based background/foreground segmantation can be found at opencv_source_code/samples/gpu/bgfg_segm.cpp */ class CV_EXPORTS_W BackgroundSubtractorMOG : public cv::BackgroundSubtractor { public: using cv::BackgroundSubtractor::apply; CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0; using cv::BackgroundSubtractor::getBackgroundImage; virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0; CV_WRAP inline void getBackgroundImage(CV_OUT GpuMat& backgroundImage, Stream& stream) { getBackgroundImage(OutputArray(backgroundImage), stream); } CV_WRAP virtual int getHistory() const = 0; CV_WRAP virtual void setHistory(int nframes) = 0; CV_WRAP virtual int getNMixtures() const = 0; CV_WRAP virtual void setNMixtures(int nmix) = 0; CV_WRAP virtual double getBackgroundRatio() const = 0; CV_WRAP virtual void setBackgroundRatio(double backgroundRatio) = 0; CV_WRAP virtual double getNoiseSigma() const = 0; CV_WRAP virtual void setNoiseSigma(double noiseSigma) = 0; }; /** @brief Creates mixture-of-gaussian background subtractor @param history Length of the history. @param nmixtures Number of Gaussian mixtures. @param backgroundRatio Background ratio. @param noiseSigma Noise strength (standard deviation of the brightness or each color channel). 0 means some automatic value. */ CV_EXPORTS_W Ptr createBackgroundSubtractorMOG(int history = 200, int nmixtures = 5, double backgroundRatio = 0.7, double noiseSigma = 0); //////////////////////////////////////////////////// // MOG2 /** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm. The class discriminates between foreground and background pixels by building and maintaining a model of the background. Any pixel which does not fit this model is then deemed to be foreground. The class implements algorithm described in @cite Zivkovic2004 . @sa BackgroundSubtractorMOG2 */ class CV_EXPORTS_W BackgroundSubtractorMOG2 : public cv::BackgroundSubtractorMOG2 { public: using cv::BackgroundSubtractorMOG2::apply; using cv::BackgroundSubtractorMOG2::getBackgroundImage; CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0; virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0; CV_WRAP inline void getBackgroundImage(CV_OUT GpuMat &backgroundImage, Stream& stream) { getBackgroundImage(OutputArray(backgroundImage), stream); } }; /** @brief Creates MOG2 Background Subtractor @param history Length of the history. @param varThreshold Threshold on the squared Mahalanobis distance between the pixel and the model to decide whether a pixel is well described by the background model. This parameter does not affect the background update. @param detectShadows If true, the algorithm will detect shadows and mark them. It decreases the speed a bit, so if you do not need this feature, set the parameter to false. */ CV_EXPORTS_W Ptr createBackgroundSubtractorMOG2(int history = 500, double varThreshold = 16, bool detectShadows = true); //! @} }} // namespace cv { namespace cuda { #endif /* OPENCV_CUDABGSEGM_HPP */