Class BackgroundSubtractorKNN

Namespace

OpenCvSharp

Assembly

OpenCvSharp.dll

K nearest neigbours algorithm

public class BackgroundSubtractorKNN : BackgroundSubtractor, IDisposable, ICvPtrHolder

Inheritance

object

DisposableObject

DisposableCvObject

Algorithm

BackgroundSubtractor

BackgroundSubtractorKNN

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

DetectShadows

Returns 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

Dist2Threshold

Gets or sets the threshold on the squared distance between the pixel and the sample. The threshold on the squared distance between the pixel and the sample to decide whether a pixel is close to a data sample.

public double Dist2Threshold { get; set; }

Property Value

double

History

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

public int History { get; set; }

Property Value

int

KNNSamples

Returns the number of neighbours, the k in the kNN. K is the number of samples that need to be within dist2Threshold in order to decide that that pixel is matching the kNN background model.

public int KNNSamples { get; set; }

Property Value

int

NSamples

Gets or sets the number of data samples in the background model

public int NSamples { 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

Methods

Create(int, double, bool)

Creates KNN Background Subtractor

public static BackgroundSubtractorKNN Create(int history = 500, double dist2Threshold = 400, bool detectShadows = true)

Parameters

history int

Length of the history.

dist2Threshold double

Threshold on the squared distance between the pixel and the sample to decide whether a pixel is close to that sample. 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

BackgroundSubtractorKNN

DisposeManaged()

Releases managed resources

protected override void DisposeManaged()