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BMOG.hpp
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BMOG.hpp
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/*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.
// Copyright (C) 2013, OpenCV Foundation, 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*/
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// Created by Isabel Martins on 10/01/17.
// adapted from OpenCV MOG2 implementation
/⁄
///////////////////////////////////////////////////////////////////////////////////////*/
#ifndef __OPENCV_BMOG_HPP__
#define __OPENCV_BMOG_HPP__
namespace cv
{
class CV_EXPORTS_W BackgroundSubtractorBMOG : public BackgroundSubtractor
{
public:
/** @brief Returns the number of last frames that affect the background model
*/
CV_WRAP virtual int getHistory() const = 0;
/** @brief Sets the number of last frames that affect the background model
*/
CV_WRAP virtual void setHistory(int history) = 0;
/** @brief Returns the number of gaussian components in the background model
*/
CV_WRAP virtual int getNMixtures() const = 0;
/** @brief Sets the number of gaussian components in the background model.
The model needs to be reinitalized to reserve memory.
*/
CV_WRAP virtual void setNMixtures(int nmixtures) = 0;//needs reinitialization!
/** @brief Returns the "background ratio" parameter of the algorithm
If a foreground pixel keeps semi-constant value for about backgroundRatio\*history frames, it's
considered background and added to the model as a center of a new component. It corresponds to TB
parameter in the paper.
*/
CV_WRAP virtual double getBackgroundRatio() const = 0;
/** @brief Sets the "background ratio" parameter of the algorithm
*/
CV_WRAP virtual void setBackgroundRatio(double ratio) = 0;
/** @brief Returns the variance threshold for the pixel-model match
The main threshold on each color component difference to decide if the sample is well described by
the background model or not. Related to Cthr from the paper.
*/
CV_WRAP virtual double getVarThreshold_L() const = 0;
CV_WRAP virtual double getVarThreshold_a() const = 0;
CV_WRAP virtual double getVarThreshold_b() const = 0;
/** @brief Sets the variance threshold for the pixel-model match
*/
CV_WRAP virtual void setVarThreshold_L(double varThreshold) = 0;
CV_WRAP virtual void setVarThreshold_a(double varThreshold) = 0;
CV_WRAP virtual void setVarThreshold_b(double varThreshold) = 0;
/** @brief Returns the variance threshold for the pixel-model match used for new mixture component generation
Threshold for each color component difference that helps decide when a sample is close to the
existing components (corresponds to Tg in the paper). If a pixel is not close to any component, it
is considered foreground or added as a new component. 3 sigma =\> Tg=3\*3=9 is default. A smaller Tg
value generates more components. A higher Tg value may result in a small number of components but
they can grow too large.
*/
CV_WRAP virtual double getVarThresholdGen() const = 0;
/** @brief Sets the variance threshold for the pixel-model match used for new mixture component generation
*/
CV_WRAP virtual void setVarThresholdGen(double varThresholdGen) = 0;
/** @brief Returns the initial variance of each gaussian component
*/
CV_WRAP virtual double getVarInit() const = 0;
/** @brief Sets the initial variance of each gaussian component
*/
CV_WRAP virtual void setVarInit(double varInit) = 0;
CV_WRAP virtual double getVarMin() const = 0;
CV_WRAP virtual void setVarMin(double varMin) = 0;
CV_WRAP virtual double getVarMax() const = 0;
CV_WRAP virtual void setVarMax(double varMax) = 0;
/** @brief Returns the complexity reduction threshold
This parameter defines the number of samples needed to accept to prove the component exists. CT=0.05
is a default value for all the samples. By setting CT=0 you get an algorithm very similar to the
standard Stauffer&Grimson algorithm.
*/
CV_WRAP virtual double getComplexityReductionThreshold() const = 0;
/** @brief Sets the complexity reduction threshold
*/
CV_WRAP virtual void setComplexityReductionThreshold(double ct) = 0;
/** @brief Returns the different learning rates depending on pixel state
*/
CV_WRAP virtual double getBkgLearningRate() const = 0;
CV_WRAP virtual double getUncoveredBkgLearningRate() const = 0;
CV_WRAP virtual double getFgLearningRate() const = 0;
CV_WRAP virtual double getStepUncoveredBkgLearningRate() const = 0;
/** @brief Sets the different learning rates depending on pixel state
*/
CV_WRAP virtual void setBkgLearningRate(double learningRate) = 0;
CV_WRAP virtual void setUncoveredBkgLearningRate(double learningRate) = 0;
CV_WRAP virtual void setFgLearningRate(double learningRate) = 0;
CV_WRAP virtual void setStepUncoveredBkgLearningRate(double stepLearningRate) = 0;
/** @brief Returns the delta
*/
CV_WRAP virtual double getDeltaTb_L() const = 0;
CV_WRAP virtual double getDeltaTb_a() const = 0;
CV_WRAP virtual double getDeltaTb_b() const = 0;
/** @brief Sets the delta
*/
CV_WRAP virtual void setDeltaTb_L(double delta) = 0;
CV_WRAP virtual void setDeltaTb_a(double delta) = 0;
CV_WRAP virtual void setDeltaTb_b(double delta) = 0;
CV_WRAP virtual int getPostProcessingMedianFilterSize() const = 0;
CV_WRAP virtual void setPostProcessingMedianFilterSize(int value) = 0;
CV_WRAP virtual int getPostProcessingMinObjectSize() const = 0;
CV_WRAP virtual void setPostProcessingMinObjectSize(int value) = 0;
//! number of initial frames using MOG2
CV_WRAP virtual int getTransientFrames() const = 0;
CV_WRAP virtual void setTransientFrames(int value) = 0;
//! selection of color space: 0->no_conversison 1->L*a*b* 2->YUV 3->YCbCr
CV_WRAP virtual int getColorSpaceConversion() const = 0;
CV_WRAP virtual void setColorSpaceConversion(int value) = 0;
//! sets previous mask externally
CV_WRAP virtual void setPreviousMask(InputArray preMask) = 0;
};
/** @brief Creates BMOG Background Subtractor
@param history Length of the history.
@param varThresholdL and varThresholdab Thresholds 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.
*/
CV_EXPORTS_W Ptr<BackgroundSubtractorBMOG>
createBackgroundSubtractorBMOG(int history=100, double varThresholdL=35, double varThresholdab=12);
//@} //video_motion
} // cv
#endif