Investigating Camera Calibration Methods for Naturalistic Driving Studies

Conference · Tue Jan 01 04:00:00 EST 2019

DOI:https://doi.org/10.2352/ISSN.2470-1173.2019.7.IRIACV-461· OSTI ID:1557534

Paone, Jeffrey R. ^[1]; Karnowski, Thomas ^[1]; Aykac, Deniz ^[1]; Ferrell, Regina ^[1]; Goddard Jr, James ^[1]; Albright, Austin P. ^[1]

---

1. ORNL

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.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE; USDOE Office of Science (SC)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1557534
• Country of Publication: United States
• Language: English