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Argus: Efficient Activity Detection System for Extended Video Analysis

  • Wenhe Liu
  • , Guoliang Kang
  • , Po Yao Huang
  • , Xiaojun Chang
  • , Lijun Yu
  • , Yijun Qian
  • , Junwei Liang
  • , Liangke Gui
  • , Jing Wen
  • , Peng Chen
  • , Alexander G. Hauptmann

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

We propose an Efficient Activity Detection System, Argus, for Extended Video Analysis in the surveillance scenario. For the spatial-temporal event detection in the surveillance video, we first generate video proposals by applying object detection and tracking algorithm which shared the detection features. After that, we extract several different features and apply sequential activity classification with them. Finally, we eliminate inaccurate events and fuse all the predictions from different features. The proposed system wins Trecvid Activities in Extended Video (ActEV1) challenge 2019. It achieves the first place with 60.5 mean weighted Pmiss, outperforming the second place system by 14.5 and the baseline R-C3D by 29.0. In TRECVID 2019 Challenge2, the proposed system wins the first place with pAUDC@0.2tfa 0.48407.

源语言英语
主期刊名Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2020
出版商Institute of Electrical and Electronics Engineers Inc.
126-133
页数8
ISBN(电子版)9781728171623
DOI
出版状态已出版 - 3月 2020
已对外发布
活动2020 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2020 - Snowmass Village, 美国
期限: 1 3月 20205 3月 2020

出版系列

姓名Proceedings - 2020 IEEE Winter Conference on Applications of Computer Vision Workshops, WACVW 2020

会议

会议2020 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2020
国家/地区美国
Snowmass Village
时期1/03/205/03/20

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