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bgdsubtractorGMG docs

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modules/video/doc/motion_analysis_and_object_tracking.rst
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@ -678,6 +678,166 @@ Sets the shadow threshold
.. ocv:function:: void BackgroundSubtractorMOG2::setShadowThreshold(double threshold)
BackgroundSubtractorGMG
------------------------
Background Subtractor module based on the algorithm given in [Gold2012]_.
.. ocv:class:: BackgroundSubtractorGMG : public BackgroundSubtractor
createBackgroundSubtractorGMG
-----------------------------------
Creates a GMG Background Subtractor
.. ocv:function:: Ptr<BackgroundSubtractorGMG> createBackgroundSubtractorGMG(int initializationFrames=120, double decisionThreshold=0.8)
.. ocv:pyfunction:: cv2.createBackgroundSubtractorGMG([, initializationFrames[, decisionThreshold]]) -> retval
:param initializationFrames: number of frames used to initialize the background models.
:param decisionThreshold: Threshold value, above which it is marked foreground, else background.
BackgroundSubtractorGMG::getNumFrames
---------------------------------------
Returns the number of frames used to initialize background model.
.. ocv:function:: int BackgroundSubtractorGMG::getNumFrames() const
BackgroundSubtractorGMG::setNumFrames
---------------------------------------
Sets the number of frames used to initialize background model.
.. ocv:function:: void BackgroundSubtractorGMG::setNumFrames(int nframes)
BackgroundSubtractorGMG::getDefaultLearningRate
--------------------------------------------------
Returns the learning rate of the algorithm. It lies between 0.0 and 1.0. It determines how quickly features are "forgotten" from histograms.
.. ocv:function:: double BackgroundSubtractorGMG::getDefaultLearningRate() const
BackgroundSubtractorGMG::setDefaultLearningRate
--------------------------------------------------
Sets the learning rate of the algorithm.
.. ocv:function:: void BackgroundSubtractorGMG::setDefaultLearningRate(double lr)
BackgroundSubtractorGMG::getDecisionThreshold
--------------------------------------------------
Returns the value of decision threshold. Decision value is the value above which pixel is determined to be FG.
.. ocv:function:: double BackgroundSubtractorGMG::getDecisionThreshold() const
BackgroundSubtractorGMG::setDecisionThreshold
--------------------------------------------------
Sets the value of decision threshold.
.. ocv:function:: void BackgroundSubtractorGMG::setDecisionThreshold(double thresh)
BackgroundSubtractorGMG::getMaxFeatures
--------------------------------------------------
Returns total number of distinct colors to maintain in histogram.
.. ocv:function:: int BackgroundSubtractorGMG::getMaxFeatures() const
BackgroundSubtractorGMG::setMaxFeatures
--------------------------------------------------
Sets total number of distinct colors to maintain in histogram.
.. ocv:function:: void BackgroundSubtractorGMG::setMaxFeatures(int maxFeatures)
BackgroundSubtractorGMG::getQuantizationLevels
--------------------------------------------------
Returns the parameter used for quantization of color-space. It is the number of discrete levels in each channel to be used in histograms.
.. ocv:function:: int BackgroundSubtractorGMG::getQuantizationLevels() const
BackgroundSubtractorGMG::setQuantizationLevels
--------------------------------------------------
Sets the parameter used for quantization of color-space
.. ocv:function:: void BackgroundSubtractorGMG::setQuantizationLevels(int nlevels)
BackgroundSubtractorGMG::getSmoothingRadius
--------------------------------------------------
Returns the kernel radius used for morphological operations
.. ocv:function:: int BackgroundSubtractorGMG::getSmoothingRadius() const
BackgroundSubtractorGMG::setSmoothingRadius
--------------------------------------------------
Sets the kernel radius used for morphological operations
.. ocv:function:: void BackgroundSubtractorGMG::setSmoothingRadius(int radius)
BackgroundSubtractorGMG::getUpdateBackgroundModel
--------------------------------------------------
Returns the status of background model update
.. ocv:function:: bool BackgroundSubtractorGMG::getUpdateBackgroundModel() const
BackgroundSubtractorGMG::setUpdateBackgroundModel
--------------------------------------------------
Sets the status of background model update
.. ocv:function:: void BackgroundSubtractorGMG::setUpdateBackgroundModel(bool update)
BackgroundSubtractorGMG::getMinVal
--------------------------------------------------
Returns the minimum value taken on by pixels in image sequence. Usually 0.
.. ocv:function:: double BackgroundSubtractorGMG::getMinVal() const
BackgroundSubtractorGMG::setMinVal
--------------------------------------------------
Sets the minimum value taken on by pixels in image sequence.
.. ocv:function:: void BackgroundSubtractorGMG::setMinVal(double val)
BackgroundSubtractorGMG::getMaxVal
--------------------------------------------------
Returns the maximum value taken on by pixels in image sequence. e.g. 1.0 or 255.
.. ocv:function:: double BackgroundSubtractorGMG::getMaxVal() const
BackgroundSubtractorGMG::setMaxVal
--------------------------------------------------
Sets the maximum value taken on by pixels in image sequence.
.. ocv:function:: void BackgroundSubtractorGMG::setMaxVal(double val)
BackgroundSubtractorGMG::getBackgroundPrior
--------------------------------------------------
Returns the prior probability that each individual pixel is a background pixel.
.. ocv:function:: double BackgroundSubtractorGMG::getBackgroundPrior() const
BackgroundSubtractorGMG::setBackgroundPrior
--------------------------------------------------
Sets the prior probability that each individual pixel is a background pixel.
.. ocv:function:: void BackgroundSubtractorGMG::setBackgroundPrior(double bgprior)
calcOpticalFlowSF
-----------------
Calculate an optical flow using "SimpleFlow" algorithm.
@ -690,7 +850,7 @@ Calculate an optical flow using "SimpleFlow" algorithm.
:param next: Second 8-bit 3-channel image of the same size as ``prev``
:param flow: computed flow image that has the same size as ``prev`` and type ``CV_32FC2``
:param flow: computed flow image that has the same size as ``prev`` and type ``CV_32FC2``
:param layers: Number of layers
@ -812,6 +972,8 @@ Releases all inner buffers.
.. [Zach2007] C. Zach, T. Pock and H. Bischof. "A Duality Based Approach for Realtime TV-L1 Optical Flow", In Proceedings of Pattern Recognition (DAGM), Heidelberg, Germany, pp. 214-223, 2007
.. [Zivkovic2004] Z. Zivkovic. Improved adaptive Gausian mixture model for background subtraction*, International Conference Pattern Recognition, UK, August, 2004, http://www.zoranz.net/Publications/zivkovic2004ICPR.pdf. The code is very fast and performs also shadow detection. Number of Gausssian components is adapted per pixel.
.. [Zivkovic2004] Z. Zivkovic. "Improved adaptive Gausian mixture model for background subtraction", International Conference Pattern Recognition, UK, August, 2004, http://www.zoranz.net/Publications/zivkovic2004ICPR.pdf. The code is very fast and performs also shadow detection. Number of Gausssian components is adapted per pixel.
.. [Zivkovic2006] Z.Zivkovic, F. van der Heijden. "Efficient Adaptive Density Estimation per Image Pixel for the Task of Background Subtraction", Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006.
.. [Gold2012] Andrew B. Godbehere, Akihiro Matsukawa, Ken Goldberg, "Visual Tracking of Human Visitors under Variable-Lighting Conditions for a Responsive Audio Art Installation", American Control Conference, Montreal, June 2012.