Adapted Windows Detection of Moving Objects in Video Scenes

This paper presents a fast method for detecting textured objects moving in a video sequence. It is based on a known background estimation and a fixed camera position. The algorithm is able to detect the presence of moving objects and locates them on-line. It is a frame-by-frame method. First, a difference image is computed from the background and the current frame. This yields three classes of pixels, those for which something changed with respect to the background, those for which nothing changed, and finally the pixels for which no decision can be made. Then an a contrario model allows an automatic clustering, by using adapted rectangular windows, of the pixels for which changes have been detected. If necessary, these regions are corrected in order to better fit the moving objects' boundaries. Experimental results show that the algorithm is very robust with respect to noise and to the quality of the background estimation. The choice of the model parameters is quite natural and user friendly. The algorithm has been successfully tested on video sequences coming from different databases, including indoor and outdoor sequences.