通过对人眼跟踪机制的研究，提出了一种新的基于多线索的目标跟踪方法。该方法采用串行结构处理多个视觉线索，首先按近邻原则产生若干候选目标，然后使用不同线索按优先级顺序逐次对候选目标进行筛选，得到的唯一候选目标再经过校正以获得更为准确的跟踪结果。该方法最大的特点是跟踪系统对环境和场景的变化有很强的自组织和自适应能力，系统内多个线索在跟踪过程中的竞争与协同使得跟踪具有强大的适应力和生命力。实验结果表明，该方法显著地提高了跟踪的鲁棒性和准确性。

In this paper a novel approach for object tracking using multiple cues is presented, based on the investigation of human eye tracking. In this approach, multiple cues with serial structure are used in tracking. First, some candidate objects are found through near neighbor principle. Then multiple cues with different priorities select the candidates in order. At last, the only survive candidate is fined by the modified module to get more accurate tracking result. The most salient characteristic of this approach is the principles of self organization and self adaptation of the changing environment during tracking. Multiple cues compete and cooperate in the system, which make the tracking has strong adaptation and vitality. Experiments show the robustness and accuracy of the tracking algorithm.