Skin Res Technol. 2023;29(4)
MARIN Q., HONDA T., OKANO Y., CHEREL M., PRESTAT-MARQUIS E. (2023)
DRC Co., Ltd., Osaka, Japan.
CIEL Co., Ltd., Tokyo, Japan.
Newtone Technologies, Lyon, France.
Abstract
Objectives: Representative of a panel, an average face image could be used to analyse/display skin changes while alleviating image rights constraints. Therefore, we used landmark-based deformation (warping) of individual skin images onto their panel’s average face, evaluating this approach’s relevance and possible limits.
Methods: An average front face image was constructed from images of 71 Japanese women (50–60 years old). After warping individual skin images onto this average face,
the resulting skin-warped average faces were presented to three experts who graded: forehead wrinkles, nasolabial fold, wrinkle of the corner of the lips, pore visibility and skin pigmentation homogeneity. Two experts estimated subjects’ age. Results were compared to gradings performed on original images.
Results: Inter-expert grading shows excellent to good correlation whatever image type: from 0.918 (forehead wrinkles) to 0.693 (visibility of pores). Correlations between scoring of both image types are almost always higher than inter-expert correlations (maximum: 0.939 for forehead wrinkles—minimum: 0.677 for pore visibility). Frequencies of grades/ages are similar when scoring original and skin-warped average face images. Experts scores are similar in 90.6%–99.3% of the cases. Average deviations upon scoring both image types are smaller than average inter-expert deviations on original images.
Conclusions: Scoring facial characteristics in original images and skin-warped average face images show an excellent agreement, even for perceived age, a complex feature. This opens the possibility of using this approach to grade facial skin features, monitor changes over time, and to valorise results on a face deprived of image rights.
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© 2023 John Wiley & Sons Ltd.
KEYWORDS: ageing signs, average face, claim substantiation, digital image, skin grading, statistics