In recent years, the technology of target tracking has been greatly developed, but occlusion and deformation of the target were still the major challenges in tracking algorithms. To address these problems, a tracking algorithm based on deformable parts model (DPM) was proposed. Firstly, DPM was used to represent the target object. DPM divided the target into several small parts. The feature of the target was composed of the local feature of each part and the global feature of the entire object, then DPM defined a uniform similar function based on the object feature and spatial relationship of each pair of parts. Secondly, a structured output support vector machine (structured SVM) was trained online as the classifier, the output of the structured SVM was the structured description of the object. The target in videos or image sequences could be tracked by the detection result of the classifier. Experimental results demonstrate that the proposed methods outperform other popular trackers, especially with the challenge of object′s occlusion and deformation.