Multimodal highway monitoring for robust incident detection

We present detection and tracking methods for highway monitoring based on video and audio sensors, and the combination of these two modalities. We evaluate the performance of the different systems on realistic data sets that have been recorded on Austrian highways. It is shown that we can achieve a very good performance for video-based incident detection of wrong-way drivers, still standing vehicles, and traffic jams. Algorithms for simultaneous vehicle and driving direction detection using microphone arrays were evaluated and also showed a good performance on these tasks. Robust tracking in case of difficult weather conditions is achieved through multimodal sensor fusion of video and audio sensors.