Abstract

Traffic statistics desired by road engineers and planners, and "traffic warning" systems demand real-time performance which precludes the use of batch processing. We apply recent real-time tracking techniques along with scene specific tuning of the dynamics to enable the tracker to accurately predict target location and thus reduce the amount of search and/or image processing required. The benefits of learning dynamics for accurate prediction are speed -- our tracker operates at frame rate -- and smoothing of vibration. Initial calibration of the projective relationship between the image and ground planes enables metric information to be derived from the image positions and velocities without full camera calibration. Results are presented on real-world traffic scenes showing the tracker to be both fast and robust to vibrations which are inevitable in traffic locations. 1 Introduction and Related Work Automatic surveillance of traffic has been of interest for many years. As early as ...

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