The multiple object tracking (MOT) algorithm will fail when its target is occluded or in fast motion,furthermore,it cannot recover from drifting.To solve these problems,firstly,we employ integrated information to enhance the representation of objects,which includes the target's appearance,shape and motion information.By means of the integrated information,we can accurately calculate the similarity,which is as similar as possible between the same targets and as different as possible between the different targets.Secondly,we propose a novel real-time single object tracker based on the combination of the discriminative correlation filters (DCF) and the Kalman filters,which is robust to occlusion and fast motion.Extensive experiments have been done,and results show that the proposed MOT algorithm can accurately track the target in case of occlusion or fast motion in real time.