In the framework of traditional particle filter, object is always drifted for the illumination light changing, deformation and poses changing, which affects the accuracy and robust performance of tracker. The reason is that there is not smooth in the objective function. Error will accumulate during the state updating process. A new stack particle filter is proposed to represent target model by the kernel histogram in the discrete fields. It can track the target from coarse to fine by the modified particle filter. Extensive experimental results show that the proposed algorithm performs 20% improvement in the accuracy, favorably time expedition and robustness against state-of-the-art methods.