Statistical Shape Analysis for 3D Facial Images

DOI

10.2991/aiie-15.2015.94How to use a DOI?

Keywords

facial morphology; gene; statistical learning; mean hyperplane; normalization

Abstract

Recently, the genetic association of human facial morphological variation attracts substantial attention. This study proposes a general framework for analyzing facial morphology variation using scanned 3D landmarks, and explores the phenotype features of facial morphology for identifying population root of Japanese archipelago. After registration for the dense 3D facial points, we investigate both PCA and Mean Hyperplane for exploring the facial morphological variations. Then, in order to reduce the in-population variance of statistical features, we normalize them firstly, and explore the identification of population using the combined phenotype features. Experiments show that our proposed strategy can give promising identification performances between the Mainland Japanese and the Ryukyuan.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - M. Nakatsu
AU  - X.H. Han
AU  - R. Kimura
AU  - Y.W. Chen
PY  - 2015/07
DA  - 2015/07
TI  - Statistical Shape Analysis for 3D Facial Images
BT  - Proceedings of the 2015 International Conference on Artificial Intelligence and Industrial Engineering
PB  - Atlantis Press
SP  - 337
EP  - 340
SN  - 1951-6851
UR  - https://doi.org/10.2991/aiie-15.2015.94
DO  - 10.2991/aiie-15.2015.94
ID  - Nakatsu2015/07
ER  -