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Academic Session 4-B : International Conference Presentation(Ⅳ) 국제학술발표(Ⅳ)

An Enhanced Video Anomaly Detection System for Smart City Management

초록

영어

Since the popularity of city monitoring systems has increased, surveillance videos have become more common. However, due to the massive increment of social event needs after lifting the coronavirus pandemic lockdown, the pressure of handling anomalies on government departments is growing with each passing day. In addition, surveillance cameras cannot record every corner of our city. There are still blind areas such as indoor environments and remote regions. Therefore, this paper introduces and develops an comprehensive system for video anomaly detection in smart city management, which is based on mobile phones, to enlarge the coverage of the current surveillance system. This system can capture and transmit abnormal videos. In addition, a deep learning method (VGG16) is implemented in the system to do video anomaly detection.

저자정보

  • Yuechun Wang Department of Information Science and Technology Sanda University Shanghai, China
  • Shufei Zhu School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou, China
  • Yuxuan Zhao School of AI and Advanced Computing Xi’an Jiaotong-Liverpool University Suzhou, China
  • Jie Zhang Department of Communications and Networking, School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou, China
  • Ka Lok Man Department of Computing, School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou, China Vytautas Magnus University Lithuania Kazimieras Simonavicius University Lithuania

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