CODEWITHSUNDEEP
opencvcomputer-visionbackground-subtractionmogshadow-removal
visualassit
visualassit

Reputation: 133

How to use cv::BackgroundSubtractorMOG in OpenCV?

I'm using OpenCV2.2 to implement moving objects detection with the method of Background Subtraction. And I use the Gaussian Mixture Model(GMM) method to model the background reference image.

I directly get the foreground pixels(or foreground mask) by using the class cv::BackgroundSubtractorMOG provided in OpenCV2.2. It's convenient but the foreground mask returned by cv::BackgroundSubtractorMOG is not as good as I expected. In addition, it seems that cv::BackgroundSubtractorMOG performs poorer than the method of GMM wrote in C language provided in OpenCV1.0.

The following is my code in OpenCV2.2:

cv::BackgroundSubtractorMOG mog;
mog(frame, fgMask, 0.01);

So, did I use the method in a wrong way?

By the way, does cv::BackgroundSubtractorMOG perform shadow removal on the foreground pixels?

Thank you very much.

Upvotes: 13

Views: 29599

Answers (4)

Jaime Ivan Cervantes
Jaime Ivan Cervantes

Reputation: 3697

I will recommend using the following settings to get started. Then you can start tuning your parameters:

cv::BackgroundSubtractorMOG2 mog;
mog(rawFrame,foregroundFrame,-1);
mog.set("nmixtures", 3);
mog.set("detectShadows",1);

In this example I set the MOG2 subtractor with 3 Gaussian mixtures. I also enabled shadow detection.

Upvotes: 0

mtall
mtall

Reputation: 3620

There are recent algorithms which remove backgrounds (detect foreground) far better than the standard GMM implementation in OpenCV.

For example, there is a block-based classifier cascade approach described in this journal article, along with its C++ based source code.

Upvotes: 5

austin
austin

Reputation: 1008

F.X.'s answer on this thread gives sample parameters of

backgroundSubtractor = new BackgroundSubtractorMOG(3, 4, 0.8);

Upvotes: 1

Jav_Rock
Jav_Rock

Reputation: 22245

When you create mog, you are not defining any parameters, so it is created with default parameters. Here you have a description of each parameter, maybe is just that. Try with 3, 4 5 Gaussians.

This function does not perforn shadow-removal but you have this other function that does. Good luck!

Upvotes: 12

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