Multimodal highway monitoring for robust incident detection
by Pucher, Michael, Schabus, Dietmar, Schallauer, Peter, Lypetskyy, Yuriy, Graf, Franz, Rainer, Harald, Stadtschnitzer, Michael, Sternig, Sabine, Birchbauer, Josef, Schneider, Wolfgang and Schalko, Bernhard
Abstract:
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.
Reference:
Multimodal highway monitoring for robust incident detection (Pucher, Michael, Schabus, Dietmar, Schallauer, Peter, Lypetskyy, Yuriy, Graf, Franz, Rainer, Harald, Stadtschnitzer, Michael, Sternig, Sabine, Birchbauer, Josef, Schneider, Wolfgang and Schalko, Bernhard), In Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems (ITSC), 2010.
Bibtex Entry:
@InProceedings{Pucher2010b, Title = {Multimodal highway monitoring for robust incident detection}, Author = {Pucher, Michael and Schabus, Dietmar and Schallauer, Peter and Lypetskyy, Yuriy and Graf, Franz and Rainer, Harald and Stadtschnitzer, Michael and Sternig, Sabine and Birchbauer, Josef and Schneider, Wolfgang and Schalko, Bernhard}, Booktitle = {Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems (ITSC)}, Year = {2010}, Address = {Madeira, Portugal}, Month = sep, Pages = {837-842}, Abstract = {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.}, Comment = {<br>Try to spot me in <a href="http://itsc2010.isr.uc.pt/site/sites/default/files/GroupPhoto_NormalPrintSize_10x15cm.jpg">this photograph</a>}, Doi = {10.1109/ITSC.2010.5625035}, File = {/download/pucher_ITSC_2010}, ISSN = {2153-0009}, Owner = {schabus}, Timestamp = {2014.09.16} }