Paper
5 March 2014 An integrated framework for detecting suspicious behaviors in video surveillance
Thi Thi Zin, Pyke Tin, Hiromitsu Hama, Takashi Toriu
Author Affiliations +
Proceedings Volume 9026, Video Surveillance and Transportation Imaging Applications 2014; 902614 (2014) https://doi.org/10.1117/12.2041232
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States
Abstract
In this paper, we propose an integrated framework for detecting suspicious behaviors in video surveillance systems which are established in public places such as railway stations, airports, shopping malls and etc. Especially, people loitering in suspicion, unattended objects left behind and exchanging suspicious objects between persons are common security concerns in airports and other transit scenarios. These involve understanding scene/event, analyzing human movements, recognizing controllable objects, and observing the effect of the human movement on those objects. In the proposed framework, multiple background modeling technique, high level motion feature extraction method and embedded Markov chain models are integrated for detecting suspicious behaviors in real time video surveillance systems. Specifically, the proposed framework employs probability based multiple backgrounds modeling technique to detect moving objects. Then the velocity and distance measures are computed as the high level motion features of the interests. By using an integration of the computed features and the first passage time probabilities of the embedded Markov chain, the suspicious behaviors in video surveillance are analyzed for detecting loitering persons, objects left behind and human interactions such as fighting. The proposed framework has been tested by using standard public datasets and our own video surveillance scenarios.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thi Thi Zin, Pyke Tin, Hiromitsu Hama, and Takashi Toriu "An integrated framework for detecting suspicious behaviors in video surveillance", Proc. SPIE 9026, Video Surveillance and Transportation Imaging Applications 2014, 902614 (5 March 2014); https://doi.org/10.1117/12.2041232
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Video surveillance

Motion models

Systems modeling

Distance measurement

Velocity measurements

Feature extraction

Image processing

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