94 lines
4.9 KiB
C++
94 lines
4.9 KiB
C++
/*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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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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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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#include "precomp.hpp"
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#include "opencv2/video/video.hpp"
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namespace cv
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{
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///////////////////////////////////////////////////////////////////////////////////////////////////////////
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CV_INIT_ALGORITHM(BackgroundSubtractorMOG, "BackgroundSubtractor.MOG",
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obj.info()->addParam(obj, "history", obj.history);
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obj.info()->addParam(obj, "nmixtures", obj.nmixtures);
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obj.info()->addParam(obj, "backgroundRatio", obj.backgroundRatio);
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obj.info()->addParam(obj, "noiseSigma", obj.noiseSigma));
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///////////////////////////////////////////////////////////////////////////////////////////////////////////
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CV_INIT_ALGORITHM(BackgroundSubtractorMOG2, "BackgroundSubtractor.MOG2",
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obj.info()->addParam(obj, "history", obj.history);
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obj.info()->addParam(obj, "nmixtures", obj.nmixtures);
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obj.info()->addParam(obj, "varThreshold", obj.varThreshold);
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obj.info()->addParam(obj, "detectShadows", obj.bShadowDetection));
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///////////////////////////////////////////////////////////////////////////////////////////////////////////
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CV_INIT_ALGORITHM(BackgroundSubtractorGMG, "BackgroundSubtractor.GMG",
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obj.info()->addParam(obj, "maxFeatures", obj.maxFeatures,false,0,0,
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"Maximum number of features to store in histogram. Harsh enforcement of sparsity constraint.");
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obj.info()->addParam(obj, "learningRate", obj.learningRate,false,0,0,
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"Adaptation rate of histogram. Close to 1, slow adaptation. Close to 0, fast adaptation, features forgotten quickly.");
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obj.info()->addParam(obj, "initializationFrames", obj.numInitializationFrames,false,0,0,
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"Number of frames to use to initialize histograms of pixels.");
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obj.info()->addParam(obj, "quantizationLevels", obj.quantizationLevels,false,0,0,
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"Number of discrete colors to be used in histograms. Up-front quantization.");
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obj.info()->addParam(obj, "backgroundPrior", obj.backgroundPrior,false,0,0,
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"Prior probability that each individual pixel is a background pixel.");
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obj.info()->addParam(obj, "smoothingRadius", obj.smoothingRadius,false,0,0,
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"Radius of smoothing kernel to filter noise from FG mask image.");
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obj.info()->addParam(obj, "decisionThreshold", obj.decisionThreshold,false,0,0,
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"Threshold for FG decision rule. Pixel is FG if posterior probability exceeds threshold."));
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bool initModule_video(void)
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{
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bool all = true;
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all &= !BackgroundSubtractorMOG_info_auto.name().empty();
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all &= !BackgroundSubtractorMOG2_info_auto.name().empty();
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all &= !BackgroundSubtractorGMG_info_auto.name().empty();
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return all;
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}
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}
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