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Conference Paper Detection of High-Risk Intoxicated Passengers in Video Surveillance
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Authors
Jae-Yeong Lee, Sunglok Choi, Jaeho Lim
Issue Date
2018-11
Citation
International Conference on Advanced Video and Signal-based Surveillance (AVSS) 2018, pp.283-303
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/AVSS.2018.8639485
Abstract
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.
KSP Keywords
Abnormal behavior, Behavior pattern, Bounding Box, High risk, Motion trajectory, Real environment, Surveillance video, Visual Features, aspect ratio, video surveillance