To cope with the drift problem of tracking caused by environmental changes (such as illumination variations and occlusions)

we propose a multi-target tracking algorithm with a hierarchical associative structure

which first coarsely matches the targets and then accurately locates them using Particle Swarm Optimization (PSO). Compared with the state-of-the-art tracking algorithms

context information is integrated into the generation of the particles during the coarse matching stage in this paper

thus enhancing the accuracy of target matching as well as reducing the number of false-tracked targets. To ensure the tracking accuracy

the targets' locations with prominent deviations in the phase of accurate tracking are rectified via Metropolis-Hastings algorithm; meanwhile

the targets' templates are updated. Experimental results show that the proposed algorithm can track the occluded targets more accurately under the occlusions.