A fast method for moving object detection in video surveillance image

Moving object detection and extraction are widely used in video surveillance and image processing. In this paper, we present a fast method for moving object detection. We use weights of the Gaussian distribution as decision factors, update parameters of the Gaussian mixture model if its values are smaller than that of those not belonging to the background; otherwise, no updates are done. It improves the existing methods by updating the Gaussian mixture model selectively. Experimental results on various scenes of video surveillance show that computation time of the proposed method is reduced.