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BackgroundSubtractorMOG2 Class
The class implements the following algorithm: "Improved adaptive Gaussian mixture model for background subtraction" Z.Zivkovic International Conference Pattern Recognition, UK, August, 2004.
Inheritance Hierarchy

Namespace:  Emgu.CV
Assembly:  Emgu.CV.World (in Emgu.CV.World.dll) Version: (
public class BackgroundSubtractorMOG2 : UnmanagedObject, 
	IBackgroundSubtractor, IAlgorithm

The BackgroundSubtractorMOG2 type exposes the following members.

Public methodBackgroundSubtractorMOG2
Create an "Improved adaptive Gaussian mixture model for background subtraction".
Public propertyAlgorithmPtr
Pointer to the unmanaged Algorithm object
Public propertyBackgroundRatio
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.
Public propertyBackgroundSubtractorPtr
Pointer to the unmanaged BackgroundSubtractor object
Public propertyComplexityReductionThreshold
The maximum variance
Public propertyDetectShadows
If true, the algorithm detects shadows and marks them.
Public propertyHistory
The number of last frames that affect the background model
Public propertyNMixtures
The number of gaussian components in the background model
Public propertyPtr
Pointer to the unmanaged object
(Inherited from UnmanagedObject.)
Public propertyShadowThreshold
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.
Public propertyShadowValue
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.
Public propertyVarInit
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.
Public propertyVarMax
The minimum variance
Public propertyVarMin
The initial variance of each gaussian component
Public propertyVarThreshold
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.
Public propertyVarThresholdGen
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 =%gt
Public methodDispose
The dispose function that implements IDisposable interface
(Inherited from DisposableObject.)
Protected methodDisposeObject
Release all the unmanaged memory associated with this background model.
(Overrides DisposableObjectDisposeObject.)
Public methodEquals (Inherited from Object.)
Protected methodFinalize
(Inherited from DisposableObject.)
Public methodGetHashCode (Inherited from Object.)
Public methodGetType (Inherited from Object.)
Protected methodMemberwiseClone (Inherited from Object.)
Protected methodReleaseManagedResources
Release the managed resources. This function will be called during the disposal of the current object. override ride this function if you need to call the Dispose() function on any managed IDisposable object created by the current object
(Inherited from DisposableObject.)
Public methodToString (Inherited from Object.)
Protected field_ptr
A pointer to the unmanaged object
(Inherited from UnmanagedObject.)
Extension Methods
Public Extension MethodApply
Update the background model
(Defined by BackgroundSubtractorExtension.)
Public Extension MethodClear
Clear the algorithm
(Defined by AlgorithmExtensions.)
Public Extension MethodGetBackgroundImage
Computes a background image.
(Defined by BackgroundSubtractorExtension.)
Public Extension MethodGetDefaultName
Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.
(Defined by AlgorithmExtensions.)
Public Extension MethodIsEmpty
Returns true if the Algorithm is empty. e.g. in the very beginning or after unsuccessful read.
(Defined by AlgorithmExtensions.)
Public Extension MethodLoad
Loads algorithm from the file
(Defined by AlgorithmExtensions.)
Public Extension MethodLoadFromString
Loads algorithm from a String
(Defined by AlgorithmExtensions.)
Public Extension MethodRead
Reads algorithm parameters from a file storage.
(Defined by AlgorithmExtensions.)
Public Extension MethodSave
Save the algorithm to file
(Defined by AlgorithmExtensions.)
Public Extension MethodSaveToString
Save the algorithm to a string
(Defined by AlgorithmExtensions.)
Public Extension MethodWrite(FileStorage)Overloaded.
Stores algorithm parameters in a file storage
(Defined by AlgorithmExtensions.)
Public Extension MethodWrite(FileStorage, String)Overloaded.
Stores algorithm parameters in a file storage
(Defined by AlgorithmExtensions.)
See Also