Automated Neoclassical Vertical Canon Validation in Human Faces with Machine Learning

Ashwinee Mehta, Maged Abdelaal, Moamen Sheba, Nic Herndon

2022

Abstract

The proportions defined by the neoclassical canons for face evaluation were developed by artists and anatomists in the 17th and 18 th centuries. These proportions are used as a reference for planning facial or dental reconstruction treatments. However, the assumption that the face is divided vertically into three equal thirds, which was adopted a long time ago, has not been verified yet. We used photos freely available online, annotated them with anthropometric landmarks using machine learning, and verified this hypothesis. Our results indicate that the vertical dimensions of the face are not always divided equally into thirds. Thus, this vertical canon should be used with caution in cosmetic, plastic, or dental surgeries, and reconstruction procedures.

Paper Citation

in Harvard Style

Mehta A., Abdelaal M., Sheba M. and Herndon N. (2022). Automated Neoclassical Vertical Canon Validation in Human Faces with Machine Learning. In Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-583-8, pages 461-467. DOI: 10.5220/0011300200003269

in Bibtex Style

@conference{data22,
author={Ashwinee Mehta and Maged Abdelaal and Moamen Sheba and Nic Herndon},
title={Automated Neoclassical Vertical Canon Validation in Human Faces with Machine Learning},
booktitle={Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2022},
pages={461-467},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011300200003269},
isbn={978-989-758-583-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Automated Neoclassical Vertical Canon Validation in Human Faces with Machine Learning
SN - 978-989-758-583-8
AU - Mehta A.
AU - Abdelaal M.
AU - Sheba M.
AU - Herndon N.
PY - 2022
SP - 461
EP - 467
DO - 10.5220/0011300200003269