A similarity-window based background estimation approach

Background estimation is one of the most challenging phases in extracting foreground objects from video sequences. In this paper we present a background modeling approach that uses the similarity of frames to extract background areas from the video sequence. We use a window over the frames history and compute the similarity between the selected frames of this window as a similarity window. The properties of similarity window depend on the characteristics of the scene and can be adjusted parametrically. Our primary results show that if proper parameters are chosen, this method can give a good approximation of the background model.