FisheyeSuperPoint: Keypoint Detection and Description Network for Fisheye Images

Anna Konrad, Anna Konrad, Ciarán Eising, Ganesh Sistu, John McDonald, Rudi Villing, Senthil Yogamani

2022

Abstract

Keypoint detection and description is a commonly used building block in computer vision systems particularly for robotics and autonomous driving. However, the majority of techniques to date have focused on standard cameras with little consideration given to fisheye cameras which are commonly used in urban driving and automated parking. In this paper, we propose a novel training and evaluation pipeline for fisheye images. We make use of SuperPoint as our baseline which is a self-supervised keypoint detector and descriptor that has achieved state-of-the-art results on homography estimation. We introduce a fisheye adaptation pipeline to enable training on undistorted fisheye images. We evaluate the performance on the HPatches benchmark, and, by introducing a fisheye based evaluation method for detection repeatability and descriptor matching correctness, on the Oxford RobotCar dataset.

Paper Citation

in Harvard Style

Konrad A., Eising C., Sistu G., McDonald J., Villing R. and Yogamani S. (2022). FisheyeSuperPoint: Keypoint Detection and Description Network for Fisheye Images. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5, SciTePress, pages 340-347. DOI: 10.5220/0010795400003124

in Bibtex Style

@conference{visapp22,
author={Anna Konrad and Ciarán Eising and Ganesh Sistu and John McDonald and Rudi Villing and Senthil Yogamani},
title={FisheyeSuperPoint: Keypoint Detection and Description Network for Fisheye Images},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={340-347},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010795400003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - FisheyeSuperPoint: Keypoint Detection and Description Network for Fisheye Images
SN - 978-989-758-555-5
AU - Konrad A.
AU - Eising C.
AU - Sistu G.
AU - McDonald J.
AU - Villing R.
AU - Yogamani S.
PY - 2022
SP - 340
EP - 347
DO - 10.5220/0010795400003124
PB - SciTePress