IP-distributed computer-aided video-surveillance system

We present a generic, flexible and robust approach for an intelligent real-time video-surveillance 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. Data flows are transmitted between the different modules using multicast technology, video flows are compressed with the MPEG-4 standard and 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. The 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 storing them with appropriate descriptions. This indexation process allows one to browse rapidly 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 a 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. (5 pages)