Real-time Control of Video Surveillance Systems with Program Supervision Techniques

International audienceIn this article, we describe a knowledge-based controlled platform using program supervision techniques. This platform eases the creation and the configuration of video surveillance systems. Several issues need to be addressed to provide a correct system configuration: (1) to choose, among a library of programs, those which are best satisfying a given user request, (2) to assign a correct value for each program parameter, (3) to evaluate performances and to guarantee a performance rate which is satisfactory regarding end-user requirements. This platform is composed of three main components: the library of programs, the knowledge base and the control component. The knowledge is either given by experts or learnt by the system. The control is generic in the sense that it is independent of any application. To validate this platform, we have built and evaluated six video surveillance systems which are featured with three properties: adaptability, reliability and real-time processing

The Imalab Method for Vision Systems

Abstract. We propose a method to construct computer vision systems using a workbench composed of a multi-faceted toolbox and a general purpose kernel. The toolbox is composed of an open set of library modules. The kernel facilitates incremental dynamic system construction. This method makes it possible to quickly develop and experiment new algorithms, it simplifies the reuse of existing program libraries, and allows to construct a variety of systems to meet particular requirements. Major strong points of our approach are: (1) Imalab is a homogeneous environment for different types of users, who share the same basic code with different interfaces and tools. (2) Integration facility: modules for various scientific domains, in particular robotics or AI research (e.g. Bayesian reasoning, symbolic learning) can be integrated automatically. (3) Multilanguage integration: the C/C++ language and several symbolic programming languages- Lisp(Scheme), Prolog, Clips- are completely integrated. We consider this an important advantage for the implementation of cognitive vision functionalities. (4) Automatic program generation, to make multi-language integration work smoothly. (5) Efficiency: library code runs without overhead. The Imalab system is in use for several years now, and we have started to distribute it.