Video security is becoming more and more important today, as the number of installed cameras can attest. There are many challenging commercial applications to monitor people or vehicle traffic. The work reported here has both research and commercial motivations. Our goals are first to obtain an efficient intelligent system that can meet strong industrial surveillance system requirements and therefore be real-time, distributed, generic and robust. Our second goal is to have a development platform that allows researchers to conceive and easily test new vision algorithms thanks to its modularity and easy setup. This paper focuses on the image analysis modules. It considers the different kind of inputs, algorithm models as well as delay and the need of generality.

Video security is becoming more and more important today, as the number of installed cameras can attest. There are many challenging commercial applications to monitor people or vehicle traffic. The work reported here has both research and commercial motivations. Our goals are first to obtain an efficient intelligent system that can meet strong industrial surveillance system requirements and therefore be real-time, distributed, generic and robust. Our second goal is to have a development platform that allows researchers to imagine and easily test new vision algorithms thanks to its modularity and easy setup. Previous papers [4,7] dealt with the core architecture for handling such problems as heterogeneous inputs, encoding, distribution, and storage. This paper will focus more precisely on the image analysis modules. We will consider the different kind of inputs, algorithm models as well as optimisation of memory, delay and genericity needs.