A target tracking algorithm based on two-level implicit shape model is proposed to solve the tracking problem under occlusion and improve the location accuracy. Firstly, partial key points about the target and surrounding areas were extracted to build the codebook dictionary by Fast Hessian detector, and the feature description vectors of the codebook were constructed by SURF descriptor to establish the codebook support model. Secondly, the symbiotic relationship between the codebook dictionary set and target was established through the generalized Hough transform, and the online updating was accomplished by the implicit shape model. Finally, by finding the maximum value in the voting space, the target was located. According to the occlusion states in the tracking process, different voting weights were assigned to the codebook of target itself and surrounding area respectively, in order to improve the location accuracy under different occlusions. Experiments show the algorithm can locate the target robustly even though the target is occlusive, or even not visible, or returns to the field of view after missing.