For the multi-target tracking problem of complex backgrounds, the models of appearance, disappearance and occlusion of target in observation scene were described, and a probabilistic multi-target tracking algorithm based on particle filter was proposed. The variable number of targets was modeled by a Markov chain, and a hidden variable was augmented in state representation to represent possible occlusion explicitly. An exclusion principle based on observation likelihood was constructed with the spatial histogram of the target, and the state and number of targets were estimated by the posterior probability. The experimental results show that the proposed algorithm is robust to the problems, such as variable target number, the similar appearance disturbance, and short-time occlusion.