Class BackgroundSubtractorMOG2

Namespace

OpenCvSharp

Assembly

OpenCvSharp.dll

The 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.

public class BackgroundSubtractorMOG2 : BackgroundSubtractor, IDisposable, ICvPtrHolder

Inheritance

object

DisposableObject

DisposableCvObject

Algorithm

BackgroundSubtractor

BackgroundSubtractorMOG2

Implements

IDisposable

ICvPtrHolder

Inherited Members

BackgroundSubtractor.Apply(InputArray, OutputArray, double)

BackgroundSubtractor.GetBackgroundImage(OutputArray)

Algorithm.Write(FileStorage)

Algorithm.Read(FileNode)

Algorithm.Empty

Algorithm.Save(string)

Algorithm.GetDefaultName()

DisposableCvObject.ptr

DisposableCvObject.DisposeUnmanaged()

DisposableCvObject.CvPtr

DisposableObject.DataHandle

DisposableObject.IsDisposed

DisposableObject.IsEnabledDispose

DisposableObject.AllocatedMemory

DisposableObject.AllocatedMemorySize

DisposableObject.Dispose()

DisposableObject.Dispose(bool)

DisposableObject.AllocGCHandle(object)

DisposableObject.AllocMemory(int)

DisposableObject.NotifyMemoryPressure(long)

DisposableObject.ThrowIfDisposed()

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Properties

BackgroundRatio

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.

public double BackgroundRatio { get; set; }

Property Value

double

ComplexityReductionThreshold

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.

public double ComplexityReductionThreshold { get; set; }

Property Value

double

DetectShadows

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

public bool DetectShadows { get; set; }

Property Value

bool

History

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

public int History { get; set; }

Property Value

int

NMixtures

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

public int NMixtures { get; set; }

Property Value

int

ShadowThreshold

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.

public double ShadowThreshold { get; set; }

Property Value

double

ShadowValue

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.

public int ShadowValue { get; set; }

Property Value

int

VarInit

Gets or sets the initial variance of each gaussian component.

public double VarInit { get; set; }

Property Value

double

VarMax

public double VarMax { get; set; }

Property Value

double

VarMin

public double VarMin { get; set; }

Property Value

double

VarThreshold

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.

public double VarThreshold { get; set; }

Property Value

double

VarThresholdGen

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.

public double VarThresholdGen { get; set; }

Property Value

double

Methods

Create(int, double, bool)

Creates MOG2 Background Subtractor.

public static BackgroundSubtractorMOG2 Create(int history = 500, double varThreshold = 16, bool detectShadows = true)

Parameters

history int

Length of the history.

varThreshold double

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.

detectShadows bool

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.

Returns

BackgroundSubtractorMOG2

DisposeManaged()

Releases managed resources

protected override void DisposeManaged()