基 于 高 分 辨 率 孪 生 网 络 的 无 人 机 目 标 跟 踪 算 法

Translated title of the contribution: UAV target tracking algorithm based on high resolution siamese network

Dian Wei Wang, Chi Zhang, Jie Fang, Zhi Jie Xu

Research output: Contribution to journalArticlepeer-review

Abstract

Unmanned Aerial Vehicle (UAV) target tracking tasks are often suffer from small target size, large scale variance and frequent viewpoint change. To address these issues, in this paper, an UAV target tracking algorithm based on high-resolution siamese network is proposed. Firstly, a high-resolution network is improved as the feature extraction backbone network (Lite-high resolution network, L-HRNet), and a dynamic multi-template strategy is used to mine the inter-frame information of the video. Secondly, a multi-frame feature fusion module is constructed to obtain fusion features that are beneficial to target localization. Finally, an anchor-free strategy is selected to locate the target position and obtain accurate tracking results. The experimental results show that the success rate and accuracy of the proposed algorithm are 66.0% and 84.7% on DTB70 dataset, 65.7% and 84.3% on UAV123 dataset respectively, which improves the target tracking performance effectively.

Translated title of the contributionUAV target tracking algorithm based on high resolution siamese network
Original languageChinese (Traditional)
Pages (from-to)1426-1434
Number of pages9
JournalJilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition)
Volume54
Issue number5
DOIs
Publication statusPublished - May 2024
Externally publishedYes

Keywords

  • computer vision
  • high-resolution siamese network
  • multi-frame feature
  • target tracking
  • unmanned aerial vehicle

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