The traditional pixel based background model cannot represent the background motion efficiently. In this paper

a novel strategy is proposed to model background and track moving objects based on optical flow velocity field. Statistics on intensity

spatial and temporal information of pixels are extracted to generate the optical flow field

which is used to formulate a novel background model for tracking moving objects efficiently and exactly. This optical flow field based strategy can reduce noise generated by background motion significantly and track moving objects robustly

as illustrated in our experiments.