Real-time traffic jam detection and localization running on a smart camera

Yuriy Lipetski; Gernot Loibner; Michael Ulm; Wolfgang Ponweiser; Oliver Sidla

doi:10.1117/12.2036931

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5 March 2014 Real-time traffic jam detection and localization running on a smart camera

Yuriy Lipetski, Gernot Loibner, Michael Ulm, Wolfgang Ponweiser, Oliver Sidla

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Proceedings Volume 9026, Video Surveillance and Transportation Imaging Applications 2014; 90260M (2014) https://doi.org/10.1117/12.2036931
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

Abstract

Reliable automatic detection of traffic jam occurrences is of big significance for traffic flow analysis related applications. We present our work aimed at the application of video based real-time traffic jam detection. Our method can handle both calibrated and un-calibrated scenarios, operating in world and in image coordinate systems respectively. The method is designed to be operated on a smart camera, but is also suitable for a standard personal computer. The combination of state-of-the-art algorithms for vehicle detections and velocity estimation allows robust long-term system operation in due to the high recall rate and very low false alarm rate. The proposed method not only detects traffic jam events in real-time, but also precisely localizes traffic jams by their start and end positions per road lane. We describe also our strategy in making computationally heavy algorithms real-time capable even on hardware with a limited computing power.

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Yuriy Lipetski, Gernot Loibner, Michael Ulm, Wolfgang Ponweiser, and Oliver Sidla "Real-time traffic jam detection and localization running on a smart camera", Proc. SPIE 9026, Video Surveillance and Transportation Imaging Applications 2014, 90260M (5 March 2014); https://doi.org/10.1117/12.2036931

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