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

Fingerprint

Sensors
Monitoring
Cameras
Infrared radiation
Lasers
Experiments

Keywords

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

ASJC Scopus subject areas

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

Cite this

Intelligent video surveillance system based on event detection and rate adaptation by using multiple sensors. / Kanai, Kenji; Ogawa, Keigo; Takeuchi, Masaru; Katto, Jiro; Tsuda, Toshitaka.

In: IEICE Transactions on Communications, Vol. E101B, No. 3, 01.03.2018, p. 688-697.

Research output: Contribution to journalArticle

@article{50207baaeb414e9cbba9fa5ef5d7a515,
title = "Intelligent video surveillance system based on event detection and rate adaptation by using multiple sensors",
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.",
keywords = "Event detection, Eventdriven rate adaptation, Multi-modal sensors, Video surveillance",
author = "Kenji Kanai and Keigo Ogawa and Masaru Takeuchi and Jiro Katto and Toshitaka Tsuda",
year = "2018",
month = "3",
day = "1",
doi = "10.1587/transcom.2017NRP0011",
language = "English",
volume = "E101B",
pages = "688--697",
journal = "IEICE Transactions on Communications",
issn = "0916-8516",
publisher = "Maruzen Co., Ltd/Maruzen Kabushikikaisha",
number = "3",

}

TY - JOUR

T1 - Intelligent video surveillance system based on event detection and rate adaptation by using multiple sensors

AU - Kanai, Kenji

AU - Ogawa, Keigo

AU - Takeuchi, Masaru

AU - Katto, Jiro

AU - Tsuda, Toshitaka

PY - 2018/3/1

Y1 - 2018/3/1

N2 - 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.

AB - 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.

KW - Event detection

KW - Eventdriven rate adaptation

KW - Multi-modal sensors

KW - Video surveillance

UR - http://www.scopus.com/inward/record.url?scp=85042640228&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85042640228&partnerID=8YFLogxK

U2 - 10.1587/transcom.2017NRP0011

DO - 10.1587/transcom.2017NRP0011

M3 - Article

VL - E101B

SP - 688

EP - 697

JO - IEICE Transactions on Communications

JF - IEICE Transactions on Communications

SN - 0916-8516

IS - 3

ER -