A novel visual object tracking method based on distribution fields descriptor is proposed to solve the problem how to describe the object effectively and adapt to the change of environmental in visual tracking. Firstly, a distribution fields descriptor is used to build the object model. Then, the object is tracked by particle filter algorithm. The model is updated online. It can reduce the impact of varying illumination and partial occlusion, thereby enhancing the efficiency of object tracking. The proposed algorithm runs in real time and performs favorably against state-of-the-art algorithms on challenging sequences. The experimental results indicate that the proposed algorithm is effective for tracking and has good performance in complex scene.