Quantitative Comparison of Affine Invariant Feature Matching

Zoltán Pusztai, Levente Hajder

2017

Abstract

It is a key problem in computer vision to apply accurate feature matchers between images. Thus the comparison of such matchers is essential. There are several survey papers in the field, this study extends one of those: the aim of this paper is to compare competitive techniques on the ground truth (GT) data generated by our structured-light 3D scanner with a rotating table. The discussed quantitative comparison is based on real images of six rotating 3D objects. The rival detectors in the comparison are as follows: Harris-Laplace, Hessian-Laplace, Harris-Affine, Hessian-Affine, IBR, EBR, SURF, and MSER.

Paper Citation

in Harvard Style

Pusztai Z. and Hajder L. (2017). Quantitative Comparison of Affine Invariant Feature Matching . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-227-1, pages 515-522. DOI: 10.5220/0006263005150522

in Bibtex Style

@conference{visapp17,
author={Zoltán Pusztai and Levente Hajder},
title={Quantitative Comparison of Affine Invariant Feature Matching},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={515-522},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006263005150522},
isbn={978-989-758-227-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 6: VISAPP, (VISIGRAPP 2017)
TI - Quantitative Comparison of Affine Invariant Feature Matching
SN - 978-989-758-227-1
AU - Pusztai Z.
AU - Hajder L.
PY - 2017
SP - 515
EP - 522
DO - 10.5220/0006263005150522