A blackboard architecture for control
Artificial Intelligence
Special Section on Video Surveillance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Programming Ruby: the pragmatic programmer's guide
Programming Ruby: the pragmatic programmer's guide
Service-Oriented Architecture: Concepts, Technology, and Design
Service-Oriented Architecture: Concepts, Technology, and Design
Scalable Surveillance Software Architecture
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
Activity Topology Estimation for Large Networks of Cameras
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
A stochastic approach to tracking objects across multiple cameras
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Searching in space and time: a system for forensic analysis of large video repositories
Proceedings of the 1st international conference on Forensic applications and techniques in telecommunications, information, and multimedia and workshop
A middleware architecture for unmanned aircraft avionics
Proceedings of the 2007 ACM/IFIP/USENIX international conference on Middleware companion
Survey on contemporary remote surveillance systems for public safety
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Review: on the use of agent technology in intelligent, multisensory and distributed surveillance
The Knowledge Engineering Review
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Automated video surveillance networks are a class of sensor networks with the potential to enhance the protection of facilities such as airports and power stations from a wide range of threats. However, current systems are limited to networks of tens of cameras, not the thousands required to protect major facilities. Realising thousand camera automated surveillance networks demands middleware and architectural support; replacing the ad hoc approaches used in current systems with robust and scalable methods.This paper introduces middleware supporting both computation and communication in automated video surveillance networks. The computational approach is based on the Blackboard architectural style, which is widely used in signal processing and AI. Communication on the surveillance network follows the service oriented model, with publish/subscribe messaging; providing scalability, availability and the ability to integrate separately developed surveillance services. The middleware is demonstrated through its application to an important class of surveillance algorithms.