Composite Spatio-Temporal Event Detection in Multi-Camera Surveillance Networks

Abstract : In this paper, we present a composite event detection system for multicamera surveillance networks. The proposed framework is able to handle correlations between primitive events that are generated from either a single camera view or multiple camera views with spatial and temporal variations. Composite events are represented in the form of full binary trees, where the leaves nodes represent primitive events, the root node represents the target composite event, and the middle nodes represent defined rules. The multi-layer design of the composite events provides a great extensibility and flexibility to users in different applications. A standardized XML-style event language is designed to describe the composite events, such that inter-agent communications and event detection module construction are conveniently achieved. In our system, a set of graphical interfaces are developed for users to easily define both primitive and high-level composite events. The proposed system is designed in the distributed form, where different components of the system can be deployed on separate processors and communicating with each other over the network. The capabilities and effectiveness of our system have been demonstrated in several real life applications.
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Communication dans un congrès
Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications - M2SFA2 2008, Oct 2008, Marseille, France. 2008
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  • HAL Id : inria-00326779, version 1

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Yun Zhai, Ying-Li Tian, Arun Hampapur. Composite Spatio-Temporal Event Detection in Multi-Camera Surveillance Networks. Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications - M2SFA2 2008, Oct 2008, Marseille, France. 2008. 〈inria-00326779〉

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