Median filtering can get a good real-time background image from a short time video-steam if the moving objects are not very crowded. By using median filtering method, the background real-time update of the moving object detecting was studied based on video information, and the selection of samples of image series was researched. Moreover, the theoretical model was established, and a good background image was got. The results show that, if the time of image series samples is too short, the background image will have objects shadow. If the time of image series samples is too long, the background image is not update, which will cause errors in the detecting of the moving objects. The time length problem can be solved by selecting the appropriate image series samples based on the theoretical model proposed.