Aiming at the problem of illumination variation and partial occlusion in the object tracking, a structural local mean and local standard deviation appearance model is proposed. The object image is divided into some blocks. In each block, the local mean and local standard deviation are calculated, then, a feature vector is composed. In order to weaken the effect of the partial occlusion, an adaptive weighted value is set to each feature component. The Native Bayesian theory is applied to track the object in affine transform space. The experimental results demonstrate that the proposed tracking method performs favorably against several state-of-the-art methods.