Cameras are among the most used sensors in Advanced Driver Assistance Systems (ADAS) and autonomous vehicles for their low cost and rich stream of information. Nevertheless, they require accurate extrinsic calibration to refer external features, e.g., obstacles and road line markings, to the vehicle reference frame. In this paper, we present a real-time online calibration procedure designed to adjust the camera’s pitch and height estimates by enforcing road line markings parallelism. Differently from most of the approaches in the literature, our is not limited to straight line markings as, under the assumption of local width constancy, parallelism is enforced also in case of high curvature line markings. Furthermore, to take into account the vehicle dynamics, e.g., accelerations and braking, our estimation procedure is framed in the context of an inverted pendulum dynamical system for which a robust filter is proposed. Finally, we experimentally assess the performance of the overall approach both in simulated and real scenarios.
Advances in Real-Time Online Vehicle Camera Calibration via Road Line Markings Parallelism Enforcement*
2022 IEEE Intelligent Vehicles Symposium (IV) ; 1511-1516
2022-06-05
493474 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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