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Proceedings Paper

An integrated framework for detecting suspicious behaviors in video surveillance
Author(s): Thi Thi Zin; Pyke Tin; Hiromitsu Hama; Takashi Toriu
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Paper 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.

Paper Details

Date Published: 5 March 2014
PDF: 8 pages
Proc. SPIE 9026, Video Surveillance and Transportation Imaging Applications 2014, 902614 (5 March 2014); doi: 10.1117/12.2041232
Show Author Affiliations
Thi Thi Zin, Univ. of Miyazaki (Japan)
Pyke Tin, Osaka City Univ. (Japan)
Hiromitsu Hama, Osaka City Univ. (Japan)
Takashi Toriu, Osaka City Univ. (Japan)


Published in SPIE Proceedings Vol. 9026:
Video Surveillance and Transportation Imaging Applications 2014
Robert P. Loce; Eli Saber; Ned Lecky, Editor(s)

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