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Robust Context-Aware Tracking with Temporal Regularization

  • Tianhao Li
  • , Tingfa Xu*
  • , Yu Bai
  • , Axin Fan
  • , Ruoling Yang
  • *此作品的通讯作者
  • Beijing Institute of Technology
  • Ministry of Education in China

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

摘要

Discriminative Correlation Filters demonstrate superior capabilities, while still suffering from background clutter. The proposed context-aware correlation filter (CACF) framework effectively avoids the interference of background noise with the explicit incorporation of global context information. However, there is still sequential context information that is not considered. This work proposes a robust context-aware tracking based on hand-crafted features by adding a temporal regularization. The temporal regularization term provides temporal information for learning filter, which limits the mutation of the filter. Experiments on OTB-100 show that our tracker demonstrates excellent accuracy and significantly improves the robustness of CF trackers and those trackers in the CACF framework.

源语言英语
主期刊名Communications, Signal Processing, and Systems - Proceedings of the 8th International Conference on Communications, Signal Processing, and Systems, CSPS 2019
编辑Qilian Liang, Wei Wang, Xin Liu, Zhenyu Na, Min Jia, Baoju Zhang
出版商Springer
页858-865
页数8
ISBN(印刷版)9789811394089
DOI
出版状态已出版 - 2020
活动8th International Conference on Communications, Signal Processing, and Systems, CSPS 2019 - Urumqi, 中国
期限: 20 7月 2019 → 22 7月 2019

出版系列

姓名Lecture Notes in Electrical Engineering
卷571 LNEE
ISSN(印刷版)1876-1100
ISSN(电子版)1876-1119

会议

会议8th International Conference on Communications, Signal Processing, and Systems, CSPS 2019
国家/地区中国
市Urumqi
时期20/07/19 → 22/07/19

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