Recent advances of single-object tracking methods: A brief survey
پیشرفتهای اخیر روشهای ردیابی تک جسمی: یک مرور مختصر-2021
Single-object tracking is regarded as a challenging task in computer vision, especially in complex spatiotemporal contexts. The changes in the environment and object deformation make it difficult to track. In the last 10 years, the application of correlation filters and deep learning enhances the performance of trackers to a large extent. This paper summarizes single-object tracking algorithms based on correlation filters and deep learning. Firstly, we explain the definition of single-object tracking and analyze the components of general object tracking algorithms. Secondly, the single-object tracking algorithms proposed in the past decade are summarized according to different categories. Finally, this paper summarizes the achievements and problems of existing algorithms by analyzing experimental results and discusses the development trends.© 2021 Elsevier B.V. All rights reserved.
Keywords: Single-object tracking | Correlation filters | Deep learning | Computer vision