Visual surveillance using less ROIs of multiple non-calibrated cameras

Authors:
Takashi Nishizaki;Yoshinari Kameda;Yuichi Ohta
Affiliations:
Graduate School of Systems and Information Engineering, University of Tsukuba, Ibaraki, Japan;Graduate School of Systems and Information Engineering, University of Tsukuba, Ibaraki, Japan;Graduate School of Systems and Information Engineering, University of Tsukuba, Ibaraki, Japan
Venue:
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part I
Year:
2006

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Abstract

With a large number of surveillance cameras, it is not an easy task to determine which camera should be monitored and which region of the camera images should be checked so that all the activities and/or events in a scene are examined. We present a new method to realize effective visual surveillance under an environment in which a number of non-calibrated fixed surveillance cameras are being operated. We also show two applications that are useful for surveillance tasks based on our proposed method. One is “suggestion of associative blocks”, and the other is “dominant camera selection”. Our approach exploits co-occurrence between two regions of interest (ROIs) over the surveillance cameras, and it needs neither calibration nor supervised training. We have conducted preliminary tests with forty cameras installed in a room and a corridor next to the room, and some promising results of the two applications are shown in this paper.