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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
- 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