Structure for the Background Subtractor operation's initialization parameters. More...

#include <opencv2/gapi/video.hpp>

Collaboration diagram for cv::gapi::video::BackgroundSubtractorParams:

Public Member Functions
	BackgroundSubtractorParams ()
	default constructor More...

	BackgroundSubtractorParams (BackgroundSubtractorType op, int histLength, double thrshld, bool detect, double lRate)

Public Attributes
bool	detectShadows = true
	If true, the algorithm will detect shadows and mark them. More...

int	history = 500
	Length of the history. More...

double	learningRate = -1

BackgroundSubtractorType	operation = TYPE_BS_MOG2
	Type of the Background Subtractor operation. More...

double	threshold = 16

Detailed Description

Structure for the Background Subtractor operation's initialization parameters.

Constructor & Destructor Documentation

◆ BackgroundSubtractorParams() [1/2]

cv::gapi::video::BackgroundSubtractorParams::BackgroundSubtractorParams ( )

inline

default constructor

◆ BackgroundSubtractorParams() [2/2]

cv::gapi::video::BackgroundSubtractorParams::BackgroundSubtractorParams	(	BackgroundSubtractorType	op,
		int	histLength,
		double	thrshld,
		bool	detect,
		double	lRate
	)

inline

Full constructor

Parameters

op	MOG2/KNN Background Subtractor type.
histLength	Length of the history.
thrshld	For MOG2: Threshold on the squared Mahalanobis distance between the pixel and the model to decide whether a pixel is well described by the background model. For KNN: Threshold on the squared distance between the pixel and the sample to decide whether a pixel is close to that sample.
detect	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.
lRate	The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate.

Member Data Documentation

◆ detectShadows

bool cv::gapi::video::BackgroundSubtractorParams::detectShadows = true

If true, the algorithm will detect shadows and mark them.

◆ history

int cv::gapi::video::BackgroundSubtractorParams::history = 500

Length of the history.

◆ learningRate

double cv::gapi::video::BackgroundSubtractorParams::learningRate = -1

The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm use some automatically chosen learning rate.

◆ operation

BackgroundSubtractorType cv::gapi::video::BackgroundSubtractorParams::operation = TYPE_BS_MOG2

Type of the Background Subtractor operation.

◆ threshold

double cv::gapi::video::BackgroundSubtractorParams::threshold = 16

For MOG2: Threshold on the squared Mahalanobis distance between the pixel and the model to decide whether a pixel is well described by the background model. For KNN: Threshold on the squared distance between the pixel and the sample to decide whether a pixel is close to that sample.

The documentation for this struct was generated from the following file:

gapi/include/opencv2/gapi/video.hpp

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Public Member Functions

Public Attributes