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Volume: 31 | Article ID: art00013
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Investigating Camera Calibration Methods for Naturalistic Driving Studies
  DOI :  10.2352/ISSN.2470-1173.2019.7.IRIACV-461  Published OnlineJanuary 2019
Abstract

Naturalistic driving studies typically utilize a variety of sensors, including radar, kinematic sensors, and video cameras. While the main objective of such sensors is typically safety focused, with a goal of recording accidents and near accidents for later review, the instrumentation provides a valuable resource for a variety of transportation research. Some applications, however, require additional processing to improve the utility of the data. In this work, we describe a computer vision procedure for calibrating front view cameras for the Second Strategic Highway Research Project. A longitudinal stability study of the estimated parameters across a small sample set of cameras is presented along with a proposed procedure for calibrating a larger number of cameras from the study. A simple use case is presented as one example of the utility of this work. Finally, we discuss plans for calibrating the complete set of approximately 3000 cameras from this study.

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Jeffrey Paone, Thomas Karnowski, Deniz Aykac, Regina Ferrell, Jim Goddard, Austin Albright, "Investigating Camera Calibration Methods for Naturalistic Driving Studiesin Proc. IS&T Int’l. Symp. on Electronic Imaging: Intelligent Robotics and Industrial Applications using Computer Vision,  2019,  pp 461-1 - 461-9,  https://doi.org/10.2352/ISSN.2470-1173.2019.7.IRIACV-461

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