TY - GEN
T1 - Detection of High-Risk Intoxicated Passengers in Video Surveillance
AU - Lee, Jae Yeong
AU - Choi, Sunglok
AU - Lim, Jaeho
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - In this paper, we present a method that is able to detect abnormal behavior of intoxicated people in surveillance videos. We first describe typical behavior patterns of intoxicated people in videos and derive two visual features that distinguish them effectively. We define a motion efficiency as one feature to capture intoxicated motion and the aspect ratio of a bounding box of an object as the other to detect intoxicated postures. For the computation of the proposed visual features, the method detects and tracks individual pedestrians in videos and evaluates their motion trajectories and pose trajectories, respectively. The experimental results on the test dataset on railway platform show that the proposed method is able to detect drunken passengers effectively and robustly in a real environment.
AB - In this paper, we present a method that is able to detect abnormal behavior of intoxicated people in surveillance videos. We first describe typical behavior patterns of intoxicated people in videos and derive two visual features that distinguish them effectively. We define a motion efficiency as one feature to capture intoxicated motion and the aspect ratio of a bounding box of an object as the other to detect intoxicated postures. For the computation of the proposed visual features, the method detects and tracks individual pedestrians in videos and evaluates their motion trajectories and pose trajectories, respectively. The experimental results on the test dataset on railway platform show that the proposed method is able to detect drunken passengers effectively and robustly in a real environment.
UR - http://www.scopus.com/inward/record.url?scp=85063294406&partnerID=8YFLogxK
U2 - 10.1109/AVSS.2018.8639485
DO - 10.1109/AVSS.2018.8639485
M3 - Conference contribution
AN - SCOPUS:85063294406
T3 - Proceedings of AVSS 2018 - 2018 15th IEEE International Conference on Advanced Video and Signal-Based Surveillance
BT - Proceedings of AVSS 2018 - 2018 15th IEEE International Conference on Advanced Video and Signal-Based Surveillance
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2018
Y2 - 27 November 2018 through 30 November 2018
ER -