Real-time traffic jam detection and localization running on a smart camera
Yuriy Lipetski, Gernot Loibner, Michael A. Ulm, Wolfgang Ponweiser, Oliver Sidla · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2014
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.