A novel multiple face tracking algorithm is proposed in this paper.Multiple Mean Shift trackers are first built to enable multiple face tracking.To overcome the weakness of Mean Shift tracking，which is prone to converge to the local maximum target if tracked objects are adjacent or partially occluded，a greedy tracking method is used to pursue the targets one by one，during which a Kalman filter is first employed to locate the initial position，and then the tracked object is removed from the scene to guarantee no other Mean Shift tracker iterates the same target.An accessory window featured with local texture distribution is introduced to correspond to candidate widows and targets.Experimental results have indicated the proposed algorithm can track multiple faces robustly in real time.