IEICE TRANSACTIONS on Communications
Intelligent Video Surveillance System Based on Event Detection and Rate Adaptation by Using Multiple Sensors
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E101-B No.3 pp.688-697
- Publication Date
- 2018/03/01
- Publicized
- 2017/09/19
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2017NRP0011
- Type of Manuscript
- Special Section PAPER (Special Section on Network Resource Control and Management for IoT Services and Applications)
- Category
Authors
Kenji KANAI
Waseda University
Keigo OGAWA
Waseda University
Masaru TAKEUCHI
Waseda University
Jiro KATTO
Waseda University
Toshitaka TSUDA
Waseda University
Keyword
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Kenji KANAI, Keigo OGAWA, Masaru TAKEUCHI, Jiro KATTO, Toshitaka TSUDA, "Intelligent Video Surveillance System Based on Event Detection and Rate Adaptation by Using Multiple Sensors" in IEICE TRANSACTIONS on Communications,
vol. E101-B, no. 3, pp. 688-697, March 2018, doi: 10.1587/transcom.2017NRP0011.
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.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2017NRP0011/_p
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@ARTICLE{e101-b_3_688,
author={Kenji KANAI, Keigo OGAWA, Masaru TAKEUCHI, Jiro KATTO, Toshitaka TSUDA, },
journal={IEICE TRANSACTIONS on Communications},
title={Intelligent Video Surveillance System Based on Event Detection and Rate Adaptation by Using Multiple Sensors},
year={2018},
volume={E101-B},
number={3},
pages={688-697},
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={},
doi={10.1587/transcom.2017NRP0011},
ISSN={1745-1345},
month={March},}
Copy
TY - JOUR
TI - Intelligent Video Surveillance System Based on Event Detection and Rate Adaptation by Using Multiple Sensors
T2 - IEICE TRANSACTIONS on Communications
SP - 688
EP - 697
AU - Kenji KANAI
AU - Keigo OGAWA
AU - Masaru TAKEUCHI
AU - Jiro KATTO
AU - Toshitaka TSUDA
PY - 2018
DO - 10.1587/transcom.2017NRP0011
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E101-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2018
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.
ER -
English
