BackgroundSubtractorMOG2 Properties

Gets or sets a memory address allocated by AllocMemory.

Gets or sets the byte length of the allocated memory

Gets or sets 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.

Gets or sets 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.

Native pointer of OpenCV structure

Gets or sets a handle which allocates using cvSetData.

Gets or sets the shadow detection flag. If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorKNN for details.

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

Gets or sets the number of last frames that affect the background model.

Gets a value indicating whether this instance has been disposed.

Gets or sets a value indicating whether you permit disposing this instance.

Gets or sets the number of gaussian components in the background model.

Gets or sets 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 Cucchiara, *Detecting Moving Shadows...*, IEEE PAMI,2003.

Gets or sets 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.

Gets or sets the initial variance of each gaussian component.

Gets or sets 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.

Gets or sets 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.