Diff: opencv2/video/background_segm.hpp

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+/*M///////////////////////////////////////////////////////////////////////////////////////
+//
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+//  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.
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+// This software is provided by the copyright holders and contributors "as is" and
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+//M*/
+
+#ifndef __OPENCV_BACKGROUND_SEGM_HPP__
+#define __OPENCV_BACKGROUND_SEGM_HPP__
+
+#include "opencv2/core.hpp"
+
+namespace cv
+{
+
+//! @addtogroup video_motion
+//! @{
+
+/** @brief Base class for background/foreground segmentation. :
+
+The class is only used to define the common interface for the whole family of background/foreground
+segmentation algorithms.
+ */
+class CV_EXPORTS_W BackgroundSubtractor : public Algorithm
+{
+public:
+    /** @brief Computes a foreground mask.
+
+    @param image Next video frame.
+    @param fgmask The output foreground mask as an 8-bit binary image.
+    @param learningRate The value between 0 and 1 that indicates how fast the background model is
+    learnt. Negative parameter value makes the algorithm to use some automatically chosen learning
+    rate. 0 means that the background model is not updated at all, 1 means that the background model
+    is completely reinitialized from the last frame.
+     */
+    CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) = 0;
+
+    /** @brief Computes a background image.
+
+    @param backgroundImage The output background image.
+
+    @note Sometimes the background image can be very blurry, as it contain the average background
+    statistics.
+     */
+    CV_WRAP virtual void getBackgroundImage(OutputArray backgroundImage) const = 0;
+};
+
+
+/** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
+
+The class implements the Gaussian mixture model background subtraction described in @cite Zivkovic2004
+and @cite Zivkovic2006 .
+ */
+class CV_EXPORTS_W BackgroundSubtractorMOG2 : 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 the squared Mahalanobis distance 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() const = 0;
+    /** @brief Sets the variance threshold for the pixel-model match
+    */
+    CV_WRAP virtual void setVarThreshold(double varThreshold) = 0;
+
+    /** @brief Returns the variance threshold for the pixel-model match used for new mixture component generation
+
+    Threshold for the squared Mahalanobis distance 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 shadow detection flag
+
+    If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorMOG2 for
+    details.
+     */
+    CV_WRAP virtual bool getDetectShadows() const = 0;
+    /** @brief Enables or disables shadow detection
+    */
+    CV_WRAP virtual void setDetectShadows(bool detectShadows) = 0;
+
+    /** @brief Returns the shadow value
+
+    Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0
+    in the mask always means background, 255 means foreground.
+     */
+    CV_WRAP virtual int getShadowValue() const = 0;
+    /** @brief Sets the shadow value
+    */
+    CV_WRAP virtual void setShadowValue(int value) = 0;
+
+    /** @brief Returns the shadow threshold
+
+    A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in
+    the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel
+    is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiarra,
+    *Detecting Moving Shadows...*, IEEE PAMI,2003.
+     */
+    CV_WRAP virtual double getShadowThreshold() const = 0;
+    /** @brief Sets the shadow threshold
+    */
+    CV_WRAP virtual void setShadowThreshold(double threshold) = 0;
+};
+
+/** @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<BackgroundSubtractorMOG2>
+    createBackgroundSubtractorMOG2(int history=500, double varThreshold=16,
+                                   bool detectShadows=true);
+
+/** @brief K-nearest neigbours - based Background/Foreground Segmentation Algorithm.
+
+The class implements the K-nearest neigbours background subtraction described in @cite Zivkovic2006 .
+Very efficient if number of foreground pixels is low.
+ */
+class CV_EXPORTS_W BackgroundSubtractorKNN : 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 data samples in the background model
+    */
+    CV_WRAP virtual int getNSamples() const = 0;
+    /** @brief Sets the number of data samples in the background model.
+
+    The model needs to be reinitalized to reserve memory.
+    */
+    CV_WRAP virtual void setNSamples(int _nN) = 0;//needs reinitialization!
+
+    /** @brief Returns the threshold on the squared distance between the pixel and the sample
+
+    The threshold on the squared distance between the pixel and the sample to decide whether a pixel is
+    close to a data sample.
+     */
+    CV_WRAP virtual double getDist2Threshold() const = 0;
+    /** @brief Sets the threshold on the squared distance
+    */
+    CV_WRAP virtual void setDist2Threshold(double _dist2Threshold) = 0;
+
+    /** @brief Returns the number of neighbours, the k in the kNN.
+
+    K is the number of samples that need to be within dist2Threshold in order to decide that that
+    pixel is matching the kNN background model.
+     */
+    CV_WRAP virtual int getkNNSamples() const = 0;
+    /** @brief Sets the k in the kNN. How many nearest neigbours need to match.
+    */
+    CV_WRAP virtual void setkNNSamples(int _nkNN) = 0;
+
+    /** @brief Returns the shadow detection flag
+
+    If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorKNN for
+    details.
+     */
+    CV_WRAP virtual bool getDetectShadows() const = 0;
+    /** @brief Enables or disables shadow detection
+    */
+    CV_WRAP virtual void setDetectShadows(bool detectShadows) = 0;
+
+    /** @brief Returns the shadow value
+
+    Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0
+    in the mask always means background, 255 means foreground.
+     */
+    CV_WRAP virtual int getShadowValue() const = 0;
+    /** @brief Sets the shadow value
+    */
+    CV_WRAP virtual void setShadowValue(int value) = 0;
+
+    /** @brief Returns the shadow threshold
+
+    A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in
+    the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel
+    is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiarra,
+    *Detecting Moving Shadows...*, IEEE PAMI,2003.
+     */
+    CV_WRAP virtual double getShadowThreshold() const = 0;
+    /** @brief Sets the shadow threshold
+     */
+    CV_WRAP virtual void setShadowThreshold(double threshold) = 0;
+};
+
+/** @brief Creates KNN Background Subtractor
+
+@param history Length of the history.
+@param dist2Threshold Threshold on the squared distance between the pixel and the sample to decide
+whether a pixel is close to that sample. 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<BackgroundSubtractorKNN>
+    createBackgroundSubtractorKNN(int history=500, double dist2Threshold=400.0,
+                                   bool detectShadows=true);
+
+//! @} video_motion
+
+} // cv
+
+#endif
+