Multiple Sensor Systems collect mutually complementary aspects of dynamically evolving scenarios characterized by many stationary or temporally changing quantities of interest. The produced sensor data streams provide near real-time and often fairly precise information about position, kinematics, type, or other characteristics of relevant objects, object groups, or more generally defined quantities to be observed and tracked. Multiple Sensor Data Fusion provides higher level information from multiple sensor data by temporal data integration and exploitation of inherent complementarities and available context information. This relatively new branch of applied computer science aims at the production of comprehensive, precise, and near real-time situation pictures, which are basic for further decisions or actions.
This workshop addresses various application aspects of multiple sensor data fusion but also include methodology oriented issues of more general interest. Its 16 presentations are grouped into 4 sessions devoted to the further development of the methodical framework, advanced object tracking algorithms, image based sensor data fusion, and surveillance applications in an urban environment.