Middleware for video surveillance networks

Abstract

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.