1.6 Conclusions

This chapter has presented the state of development of intelligent distributed surveil-lance systems, including a review of current image processing techniques that are used in different modules that constitute part of surveillance systems. Looking at these image processing tasks, it has identified research areas that need to be investigated further such as adaptation, data fusion and tracking methods in a co-operative multi-sensor environment and extension of techniques to classify complex activities and interactions between detected objects. In terms of communication or integration between different modules it is necessary to study new communication protocols and the creation of metadata standards. It is also important to consider improved means of task distribution that optimise the use of central, remote facilities and data communication networks. Moreover, one of the aspects that the authors believe is essential in the coming future for the development of distributed surveillance systems is the definition of a framework to design distributed architectures firmly rooted on systems engineering best practice, as used in other disciplines such as control aerospace systems.

The growing demand for safety and security has led to more research in building more efficient and intelligent automated surveillance systems. Therefore, a future challenge is to develop a wide-are a distributed multi-sensor surveillance system which has robust, real-time computer algorithms able to perform with minimal manual reconfiguration on variable applications. Such systems should be adaptable enough to adjust automatically and cope with changes in the environment like lighting, scene geometry or scene activity. The system should...