A traffic situation analysis system

Oliver Sidla; Marcin Rosner

doi:10.1117/12.872975

24 January 2011 A traffic situation analysis system

Oliver Sidla, Marcin Rosner

Proceedings Volume 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques; 787803 (2011) https://doi.org/10.1117/12.872975
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

Abstract

The observation and monitoring of traffic with smart visions systems for the purpose of improving traffic safety has a big potential. For example embedded vision systems built into vehicles can be used as early warning systems, or stationary camera systems can modify the switching frequency of signals at intersections. Today the automated analysis of traffic situations is still in its infancy - the patterns of vehicle motion and pedestrian flow in an urban environment are too complex to be fully understood by a vision system. We present steps towards such a traffic monitoring system which is designed to detect potentially dangerous traffic situations, especially incidents in which the interaction of pedestrians and vehicles might develop into safety critical encounters. The proposed system is field-tested at a real pedestrian crossing in the City of Vienna for the duration of one year. It consists of a cluster of 3 smart cameras, each of which is built from a very compact PC hardware system in an outdoor capable housing. Two cameras run vehicle detection software including license plate detection and recognition, one camera runs a complex pedestrian detection and tracking module based on the HOG detection principle. As a supplement, all 3 cameras use additional optical flow computation in a low-resolution video stream in order to estimate the motion path and speed of objects. This work describes the foundation for all 3 different object detection modalities (pedestrians, vehi1cles, license plates), and explains the system setup and its design.

Citation Download Citation

Oliver Sidla and Marcin Rosner "A traffic situation analysis system", Proc. SPIE 7878, Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques, 787803 (24 January 2011); https://doi.org/10.1117/12.872975

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