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In this article we present a real time platform for semantic video interpretation applied to bank agency monitoring. The proposed system is a multi-camera platform, which recognizes userpredefined scenarios, such as bank attack scenarios. These scenarios are modelled by domain experts using a back and forth process and based on a representation language. In order to address bank monitoring issues, the system has been improved based on two evaluation types. First, a repair stage guided by a careful technical evaluation has been performed at each level of the interpretation chain. As a consequence, the robustness obtained was sufficient enough to recognize all scenarios of interest. Second, an end-user evaluation has helped the experts to improve the scenario models to adapt them to real life situations. We report results of scenario recognition performances on real video sequences taken in a bank agency.

In this article we present a generic, flexible and robust approach for an intelligent real-time videosurveillance system. The proposed system is a multi-camera platform that is able to handle different standards of video inputs (composite, IP, IEEE1394). The system implementation is distributed over a scalable computer cluster based on Linux and IP network. Data flows are transmitted between the different modules using multicast technology, video flows are compressed with the MPEG4 standard and the flow control is realized through a TCP-based command network (e.g. for bandwidth occupation control). The design of the architecture is optimized to display, compress, store and playback data and video flows in an efficient way. This platform also integrates advanced video analysis tools, such as motion detection, segmentation, tracking and neural networks modules. The goal of these advanced tools is to provide help to operators by detecting events of interest in visual scenes and store them with appropriate descriptions. This indexation process allows one to rapidly browse through huge amounts of stored surveillance data and play back only interesting sequences. We report here some preliminary results and we show the potential use of such a flexible system in third generation video surveillance system. We illustrate the interest of the system in a real case study, which is the surveillance of a reception desk.

In 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.