Constrained Multi Camera Calibration for Lane Merge Observation

Kai Cordes, Hellward Broszio

2019

Abstract

For the trajectory planning in autonomous driving, the accurate localization of the vehicles is required. Accurate localizations of the ego-vehicle will be provided by the next generation of connected cars using 5G. Until all cars participate in the network, un-connected cars have to be considered as well. These cars are localized via static cameras positioned next to the road. To achieve high accuracy in the vehicle localization, the highly accurate calibration of the cameras is required. Accurately measured landmarks as well as a priori knowledge about the camera configuration are used to develop the proposed constrained multi camera calibration technique. The reprojection error for all cameras is minimized using a differential evolution (DE) optimization strategy. Evaluations on data recorded on a test track show that the proposed calibration technique provides adequate calibration accuracy while the accuracies of reference implementations are insufficient.

Paper Citation

in Harvard Style

Cordes K. and Broszio H. (2019). Constrained Multi Camera Calibration for Lane Merge Observation. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP; ISBN 978-989-758-354-4, SciTePress, pages 529-536. DOI: 10.5220/0007387805290536

in Bibtex Style

@conference{visapp19,
author={Kai Cordes and Hellward Broszio},
title={Constrained Multi Camera Calibration for Lane Merge Observation},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP},
year={2019},
pages={529-536},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007387805290536},
isbn={978-989-758-354-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP
TI - Constrained Multi Camera Calibration for Lane Merge Observation
SN - 978-989-758-354-4
AU - Cordes K.
AU - Broszio H.
PY - 2019
SP - 529
EP - 536
DO - 10.5220/0007387805290536
PB - SciTePress