Symmetry-aware Registration of Human Faces

Martin Prantl, Libor Váša, Ivana Kolingerová

2019

Abstract

Registration of 3D objects is a challenging task, especially in presence of symmetric parts. A registration algorithm based on feature vectors must be able to distinguish left and right parts. Symmetric geometry can be found in those two parts, however, most popular feature vectors produce equal numbers in this case, even though the geometry is in fact different. One field, where this problem arises, is the registration of partially overlapping parts of human faces or entire heads. The symmetric parts in this case are often eyes, ears, nostrils, mouth corners etc. Using symmetry-oblivious feature vectors makes it hard to distinguish left and right part of the face or head. This paper presents a feature vector modification based on a vector field flux and curvature. Results show that the modified feature vector can improve the subsequent registration process.

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Paper Citation


in Harvard Style

Prantl M., Váša L. and Kolingerová I. (2019). Symmetry-aware Registration of Human Faces. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP; ISBN 978-989-758-354-4, SciTePress, pages 185-192. DOI: 10.5220/0007254801850192


in Bibtex Style

@conference{grapp19,
author={Martin Prantl and Libor Váša and Ivana Kolingerová},
title={Symmetry-aware Registration of Human Faces},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 1: GRAPP},
year={2019},
pages={185-192},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007254801850192},
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 1: GRAPP
TI - Symmetry-aware Registration of Human Faces
SN - 978-989-758-354-4
AU - Prantl M.
AU - Váša L.
AU - Kolingerová I.
PY - 2019
SP - 185
EP - 192
DO - 10.5220/0007254801850192
PB - SciTePress