Misa Hirose,a Saori Toyota,a Nobutoshi Ojima,b Keiko Ogawa-Ochiai c and Norimichi
Tsumuraa
a Graduate School of Advanced Integration Science, Chiba University, CHIBA, JAPAN
b Global R&D Beauty Creation, Kao Corporation, TOKYO, JAPAN
c Clinic of Japanese-Oriental (Kampo) Medicine, Department of Otorhinolaryngology & Head and Neck Surgery,
Kanazawa University Hospital, KANAZAWA, JAPAN
Optical Review 2016 (accepted)
Abstract
In this paper, principal component analysis is applied to the distribution
of pigmentation, surface reflectance, and landmarks in whole facial images
in order to obtain feature values. The relationship between the obtained
feature vectors and the age of the face is then estimated by multiple regression
analysis so that facial images can be modulated for woman aged 10 to 70.
In a previous study, we analyzed only the distribution of pigmentation,
and the reproduced images appeared to be younger than the apparent age
of the initial images. We believe that this happened because we did not
modulate the facial structures and detailed surfaces, such as wrinkles.
By considering landmarks and surface reflectance over the entire face,
we were able to analyze the variation in the distributions of facial structures
and fine asperity, and pigmentation. As a result, our method is able to
appropriately modulate the appearance of a face so that it appears to be
the correct age.
[PDF] (to appeare)