We develop and evaluate algorithms for automatic object detection and object tracking in sensor networks

The research work is focused on the detection and presentation of objects in imagery data streams of interconnected mobile sensors. In this context the technologies investigated include the aspect-independent description of objects, the registration of sensor-generated images with three-dimensional context data, and bandwidth-economical transfer of object information.

Video Content Analysis combines methods for the detection and tracking of objects in video streams with algorithms for the conceptual description and analysis of the extracted, quantitative information. The studies aim at coming up with systems for the semantic analysis of videos, which means that videos are not only analyzed quantitatively, but that the extracted information is associated to conceptual background knowledge in order to draw conclusions from the visually perceived environment.

Especially with regard to military tracking systems, performance evaluation is an essential theme. The topics "Tracking and Tracker Assessment" are dealt with on the basis of years of experience in the development and design of evaluation schemes that interrelate and evaluate both the performance ability of tracking algorithms and the risk analysis, while taking into account possible counter-measures.

Acquisition and analysis of 3D data is important if a high degree of automation and reliability of object recognition is required. The department's research activities in this field are concerned with the development, optimization and evaluation of methods for 3D data analysis for use with established sensor techniques as well as prototypical hardware. Moreover, data acquired by such sensors are used for area-wide monitoring and to provide context information for image exploitation.