Background subtraction is very useful in video surveillance. Basically, background subtraction technique performs really well for cases where we have to detect moving objects in a static scene. As the name indicates, this algorithm works by detecting the background and subtracting it from the current frame to obtain the foreground, that is, moving objects. In order to detect moving objects, we need to build a model of the background first. This is not the same as frame differencing because we are actually modeling the background and using this model to detect moving objects. So, this performs much better than the simple frame differencing technique. This technique tries to detect static parts in the scene and then include it in the background model. So, it's an adaptive technique that can adjust according to the scene.

Let's consider the following image:

Now, as we gather more frames in this scene, every part of the image will gradually become a part of the background...