Stereo Video Camera Calibration in the Wild

Arhum Sultana, Michael Jenkin

2023

Abstract

Although a number of robust stereo camera calibration algorithms exist in the literature, a common assumption of these algorithms is a representative set of calibration images containing a planar calibration target of known geometry. For stereo-video applications, it is a common practice to obtain a large number of stereo image pairs for the stereo calibration process. How should an optimal set of stereo-video calibration images be chosen when controlled camera positioning is difficult or impossible? Here we demonstrate how a greedy RANdom SAmple Consensus (RanSaC)-based approach can be used to choose the appropriate calibration image set for improved stereo camera calibration. This paper describes the performance of a greedy, RanSaC approach which is compared against a random frames selection approach. Performance is measured through mean calibration reprojection error. Evaluation on real world stereo video calibration data-sets collected in the underwater environment illustrates the effectiveness of the proposed approach.

Paper Citation

in Harvard Style

Sultana A. and Jenkin M. (2023). Stereo Video Camera Calibration in the Wild. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-670-5, SciTePress, pages 64-69. DOI: 10.5220/0012191700003543

in Bibtex Style

@conference{icinco23,
author={Arhum Sultana and Michael Jenkin},
title={Stereo Video Camera Calibration in the Wild},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2023},
pages={64-69},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012191700003543},
isbn={978-989-758-670-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Stereo Video Camera Calibration in the Wild
SN - 978-989-758-670-5
AU - Sultana A.
AU - Jenkin M.
PY - 2023
SP - 64
EP - 69
DO - 10.5220/0012191700003543
PB - SciTePress