Intelligent video surveillance system based on event detection and rate adaptation by using multiple sensors

Kenji Kanai, Keigo Ogawa, Masaru Takeuchi, Jiro Katto, Toshitaka Tsuda

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

To reduce the backbone video traffic generated by video surveillance, we propose an intelligent video surveillance system that offers multi-modal sensor-based event detection and event-driven video rate adaptation. Our proposed system can detect pedestrian existence and movements in the monitoring area by using multi-modal sensors (camera, laser scanner and infrared distance sensor) and control surveillance video quality according to the detected events. We evaluate event detection accuracy and video traffic volume in the experiment scenarios where up to six pedestrians pass through and/or stop at the monitoring area. Evaluation results conclude that our system can significantly reduce video traffic while ensuring high-quality surveillance.

Original languageEnglish
Pages (from-to)688-697
Number of pages10
JournalIEICE Transactions on Communications
VolumeE101B
Issue number3
DOIs
Publication statusPublished - 2018 Mar 1

Keywords

  • Event detection
  • Eventdriven rate adaptation
  • Multi-modal sensors
  • Video surveillance

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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