A particle filter for object tracking based on multi-region sampling is proposed to solve the problems of degeneracy phenomenon and particle impoverishment introduced by traditional particle filter algorithm. The proposed method uses some overlapping sub-regions to divide the target model, and each sub-region corresponds to a sampling windows. The true state of target can be estimated by the confidence of each sub-region. The complementary and stage uniqueness of sub-region can guarantee the validity of particles and the quality of state-space. Thereby, the accuracy of object tracking is improved. Experimental results show that the proposed method relieves effectively the sample degradation and poverty problems, improves the efficiency of particles, and is robust to pose, illumination and partial occlusion in the complex background.