Algorithmic characterization of vehicle trajectories from image sequences by motion verbs

Images of vehicles which move in traffic scenes recorded by a stationary camera have been detected and tracked without operator intervention. The resulting vehicle trajectories were projected from the image plane onto the street plane. A suitable system internal representation of about 90 German motion verbs was then exploited in order to automatically characterize trajectory segments in terms of natural language concepts. A multiresolution approach for feature matching has been developed which is robust enough to track vehicle images across hundreds of frames, despite considerable variations in size and projected velocity. Results from experiments with image sequences from real-world traffic scenes are presented.<<ETX>>