A new system for video-based detection of moving objects and its integration into digital networks

In many video surveillance applications outdoor scenes are to be observed, normally located far away from the location of the observation personnel. This application scenario yields some basic demands if video detection techniques are applied: (a) The detection scheme has to be robust against distortions like varying illumination conditions, small camera motion, trees in motion, rain, snow, etc. (b) The video images and/or detection results have to be transmitted to the surveillance center. (c) The calibration and installation effort of the sensor should be as simple as possible. In conventional schemes, an individual transmission channel is necessary for each sensor connected to a surveillance center. The costs increase with the distance and the number of connections. As a video signal is transmitted the connection needs high bandwidth. In this paper, a new system is presented which includes a video-based detection of moving objects in natural scenes and a transmission of images via digital networks. The detection and description of moving objects is based on an object-oriented, statistical multi-feature analysis of video sequences. This analysis is self-adapting to an observed scene, such that the calibration effort is very low. In case of an alarm event, object parameters are extracted and video images are memorized showing the history of the alarm event. Applying compression techniques this data are transmitted to an arbitrarily located surveillance center using digital networks