Edge-centric Video Surveillance System Based on Event-driven Rate Adaptation for 24-hour Monitoring

Airi Sakaushi, Kenji Kanai, Jiro Katto, Toshitaka Tsuda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, to sustain a high-quality 24-hour video surveillance (i.e., high reliability) and reduce redundant video traffic volume (i.e., network friendliness), we propose an edge-centric video surveillance system that provides flexible adaptive control of the image enhancement process and video quality based on an event-driven adaptation. In the proposed system, the video bitrate is adaptively controlled according to the contrast of captured videos and conditions in a monitored area (e.g., 'normal', 'caution', and 'alert'). To confirm the system performance, we evaluate objective image quality, accuracy of human detection and video traffic volume generated by the proposed system. Evaluations conclude that the system can reduce the video traffic while sustaining high-quality visibility.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages651-656
Number of pages6
ISBN (Electronic)9781538632277
DOIs
Publication statusPublished - 2018 Oct 2
Event2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018 - Athens, Greece
Duration: 2018 Mar 192018 Mar 23

Other

Other2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018
CountryGreece
CityAthens
Period18/3/1918/3/23

Keywords

  • Edge computing
  • Image enhancement
  • IoT
  • Rate adaptation
  • Video surveillance system

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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  • Cite this

    Sakaushi, A., Kanai, K., Katto, J., & Tsuda, T. (2018). Edge-centric Video Surveillance System Based on Event-driven Rate Adaptation for 24-hour Monitoring. In 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018 (pp. 651-656). [8480272] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PERCOMW.2018.8480272