Autonomous multisensor tracking surveillance system

In the world of video especially in video processing important steps are being taken at this time. Research projects around the world are tackling all kind of tracking problems and segmentation of video images. Others are doing feature extraction, image enhancements also using combinations of multiple sensors. The goal is always to help machines interpret the content of the images. Biometrical identification and verification is also becoming more and more important. What is the goal of machines interpreting video imagesΧ They can work 24 hours a day and they are efficient. This becomes very important for systems with a growing number of sensors. With a large number of sensors the coordination and control gets more and more difficult not to mention the installation and calibration. Such a system needs a good installation concept to be affordable for the end user. Also the maintenance effort needs to be reduced. This leads to integration of more functionality than only image interpretation into the sensor units. It has also to assist the installer and configurator during the commissioning of the plant. After developing video surveillance equipment for 10 years the leading thought was, that there must be a way to get complex algorithms out of the laboratories into the field. This is the reason why I developed a so called Sensorcam. This sensorcam was built with the base knowhow of the SEON1100 minidome (developed for Sensile Systems), a very small pan-tilt dome camera and the SDR2100, a digital video recorder for the commercial video surveillance market. The result is a prototype of a sensorcam network which is able to fill the gap between algorithm research and commercial products. The additional costs are minimal for the gained functionality. The goal of this work was to develop a network of pan tilt cameras which should be easy to install, calibrate, configure and maintain for an affordable price. Therefore the devices have to detect their neighbor's relative position and send that information to a central controller which can assemble that information to a complete floorplan of the sensorcam network. If such a floorplan can be constructed automatically such a system can be used as a commercial base platform for algorithms written for multisensor networks like people tracking over multiple cameras[21], tracking of targets in cluttered[16] or even occluded scenes[18]. During the development of such a camera network various sensor technologies have been selected due to their price/performance ratio. The main question was what technology to use for the first contact between neighboring sensorcam devices. Usually there is no direct sight, therefore direct visual recognition would not work. Simple radiofrequency signals do not provide geometrical information and an indoor GPS would be far too expensive. A quite common technology is infrared communication. An infrared signal source is not expensive and works over some meters distance. So the decision w