DocumentCode :
1357724
Title :
Collaborative occupancy reasoning in visual sensor network for scalable smart video surveillance
Author :
Cho, Yongil ; Lim, Sang Ok ; Yang, Hyun Seung
Author_Institution :
Dept. of Comput. Sci., Korea Adv. Inst. of Sci. & Technol. (KAIST), Daejeon, South Korea
Volume :
56
Issue :
3
fYear :
2010
Firstpage :
1997
Lastpage :
2003
Abstract :
Video surveillance is a popular consumer application that is used for various purposes such as public safety, facilities surveillance, and traffic monitoring. In a general video surveillance system, video streams from cameras are sent to a control center and operators monitor the videos. But human operator monitoring of the views every moment of every day is almost impossible; so, smart surveillance systems are required, systems that are capable of automated scene analysis. There are a number of studies to enable smart video surveillance in a multi-camera network. Most of the studies, however, treat central processing approaches in which a scene analysis is processed inside a central server domain once all available information has been collected in the server. Such approaches require tremendous efforts in building the system and, moreover, limit the scalability. To accomplish scalable smart video surveillance, an inference framework in visual sensor networks is necessary, one in which autonomous scene analysis is performed via distributed and collaborative processing among camera nodes without necessity for a high performance server. In this paper, we propose a collaborative inference framework for visual sensor networks and an efficient occupancy reasoning algorithm that is essential in smart video surveillance based on the framework. We estimate the existence probabilities for every camera and combine them using the work-tree architecture in a distributed and collaborative manner. We aim for practical smart video surveillance systems.
Keywords :
intelligent sensors; video streaming; video surveillance; automated scene analysis; autonomous scene analysis; camera nodes; cameras; collaborative inference framework; collaborative occupancy reasoning; collaborative processing; control center; distributed processing; facilities surveillance; multi-camera network; public safety; smart video surveillance; traffic monitoring; video streams; visual sensor networks; Cameras; Cognition; Semantics; Servers; Topology; Video surveillance; Visualization; Smart Video Surveillance, Distributed Inference, Visual Sensor Network, Occupancy Reasoning;
fLanguage :
English
Journal_Title :
Consumer Electronics, IEEE Transactions on
Publisher :
ieee
ISSN :
0098-3063
Type :
jour
DOI :
10.1109/TCE.2010.5606357
Filename :
5606357
Link To Document :
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