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RSVP: A real-time surveillance video parsing system with single frame supervision

  • Han Yu
  • , Guanghui Ren
  • , Ruihe Qian
  • , Yao Sun
  • , Changhu Wang
  • , Hanqing Lu
  • , Si Liu*
  • *此作品的通讯作者
  • CAS - Institute of Information Engineering
  • Toutiao AI Lab.
  • Chinese Academy of Sciences

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In this demo, we present a real-time surveillance video parsing (RSVP) system to parse surveillance videos. Surveillance video parsing, which aims to segment the video frames into several labels, e.g., face, pants, left-legs, has wide applications, especially in security filed. However, it is very tedious and time-consuming to annotate all the frames in a video. We design a RSVP system to parse the surveillance videos in real-time. The RSVP system requires only one labeled frame in training stage. The RSVP system jointly considers the segmentation of preceding frames when parsing one particular frame within the video. The RSVP system is proved to be effective and efficient in real applications.

源语言英语
主期刊名MM 2017 - Proceedings of the 2017 ACM Multimedia Conference
出版商Association for Computing Machinery, Inc
1257-1258
页数2
ISBN(电子版)9781450349062
DOI
出版状态已出版 - 23 10月 2017
已对外发布
活动25th ACM International Conference on Multimedia, MM 2017 - Mountain View, 美国
期限: 23 10月 201727 10月 2017

出版系列

姓名MM 2017 - Proceedings of the 2017 ACM Multimedia Conference

会议

会议25th ACM International Conference on Multimedia, MM 2017
国家/地区美国
Mountain View
时期23/10/1727/10/17

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