Visual Object Tracking Algorithm Based on Dynamic Template and Position Enhancement

Visual object tracking (VOT) algorithms based on Transformer have excellent tracking performance, but they often neglect historical image information and are difficult to avoid interference from similar objects. To address these issues, a Visual object tracking algorithm based on Dynamic Template and Position Enhancement is proposed in this paper. On the one hand, Dynamic Template (DT) is added to the algorithm to resolve the problem of insufficient representation of target appearance information by a single template, to obtain high-quality dynamic templates, an update strategy is proposed that is based on similarity determination at a fixed number of frames. On the other hand, a Positional Enhancement (PE) module is added to the Transformer's self-attention computation process to reduce the interference of background information on foreground information. Extensive experiments were conducted on several datasets to evaluate the proposed algorithm, which demonstrated excellent performance. The proposed algorithm also achieves an inference speed of 43 FPS. The experimental results show that the proposed algorithm can effectively handle tracking task in complex scenes.