Surveillance video cameras have been increasingly deployed on roadway networks providing important support for roadway management. While the information-rich video images are a valuable source of traffic data, these surveillance video cameras are typically designed for manual observation of roadway conditions and are not for automatic traffic data collection. The benefits of turning these surveillance cameras into data collection cameras are obvious, but collecting traffic data would normally require the development of a cost-effective method to efficiently and accurately calibrate surveillance video cameras. This paper proposes such a robust and efficient method that calibrates surveillance video cameras using standard shipping container as the reference object. The traditional camera calibration model can be simplified and camera parameters can be recovered with precise mathematical derivation. After solving for all the camera parameters, the 3D object world coordinates can be reconstructed from 2D image coordinates, thus enabling the collection of a variety of traffic data using surveillance video camera data.
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Ke et al. (2017) studied this question.