cv.BackgroundSubtractorGMG

Background Subtractor module

Background Subtractor module based on the algorithm given in [Gold2012].

Takes a series of images and returns a sequence of mask uint8 images of the same size, where 255 indicates Foreground and 0 represents Background. This class implements an algorithm described in [Gold2012].

This algorithm combines statistical background image estimation and per-pixel Bayesian segmentation. It was introduced by [Gold2012]. As per the paper, the system ran a successful interactive audio art installation called "Are We There Yet?" in 2011 at the Contemporary Jewish Museum in San Francisco, California.

It uses first few (120 by default) frames for background modelling. It employs probabilistic foreground segmentation algorithm that identifies possible foreground objects using Bayesian inference. The estimates are adaptive; newer observations are more heavily weighted than old observations to accommodate variable illumination. Several morphological filtering operations like closing and opening are done to remove unwanted noise. You will get a black window during first few frames.

References

[Gold2012]:

Andrew B Godbehere, Akihiro Matsukawa, and Ken Goldberg. "Visual Tracking of Human Visitors under Variable-Lighting Conditions for a Responsive Audio Art Installation". In American Control Conference (ACC), Montreal, 2012, pages 4305-4312. IEEE, June 2012.

Superclasses	handle
Sealed	false
Construct on load	false

BackgroundPrior	The prior probability that each individual pixel is a background
DecisionThreshold	The value of decision threshold.
DefaultLearningRate	The learning rate of the algorithm.
MaxFeatures	Total number of distinct colors to maintain in histogram.
MaxVal	The maximum value taken on by pixels in image sequence.
MinVal	The minimum value taken on by pixels in image sequence. Usually 0.
NumFrames	The number of frames used to initialize background model.
QuantizationLevels	The parameter used for quantization of color-space.
SmoothingRadius	The kernel radius, in pixels, used for morphological operations for
UpdateBackgroundModel	The status of background model update.
id	Object ID

	addlistener	Add listener for event.
	apply	Updates the background model and computes the foreground mask
	delete	Destructor
	eq	== (EQ) Test handle equality.
	findobj	Find objects matching specified conditions.
	findprop	Find property of MATLAB handle object.
	ge	>= (GE) Greater than or equal relation for handles.
	getBackgroundImage	Computes a background image
	gt	> (GT) Greater than relation for handles.
Sealed	isvalid	Test handle validity.
	le	<= (LE) Less than or equal relation for handles.
	listener	Add listener for event without binding the listener to the source object.
	lt	< (LT) Less than relation for handles.
	ne	~= (NE) Not equal relation for handles.
	notify	Notify listeners of event.