In the past decade,benefitting from the progress in computer vision theories and computing resources,there has been a rapid development in visual object tracking. Among all the methods,the tracklet-based object tracking method has gained its popularity due to its robustness in occlusion scenarios and high computational efficiency. This paper present a comprehensive survey of research methods related to tracklet-based object tracking. First,the basic concepts,research significance and research status of visual object tracking are introduced briefly. Then,the tracklet-based tracking approach is described from four aspects,including object detection,feature extraction,tracklet generation,and tracklet association and completion. Afterwards,we propose a detailed review and analyze the characteristics of state-of-the-art tracklet-based tracking methods. Finally, potential challenges and research fields are discussed. In our opinion, more advanced object tracking models should be proposed and the parallel vision approach should be adopted to learn and evaluate tracking models in a virtual-real interactive way.