Long-Term Face Image Analysis Based on Canonical Correlation Analysis on Physical and Psychological Evaluation of Face

Abstract

In this paper, we analyze the relationship between impression of facial skin and skin pigmentation distribution by applying Canonical Coefficient Analysis (CCA) to multiple physical and psychological features obtained from facial skin. Based on the acquired relationship expression, we modulate the skin pigment features, and appearances of the face with arbitrary psychological features are reproduced. In our previous work, we applied principal component analysis (PCA) to the melanin pigment variation of the facial skin, and we obtained individual differences in it occurring over seven years. In the previous method, as the factor causing individual difference, we considered the frequency of UV care. However, actual skin appearance is thought to depend not only on melanin but also on several other factors. Therefore, in this study, we photographed the faces of women of various ages for 12 years, and at the same time obtained psychological features of appearance. As physical features, melanin and hemoglobin pigmentation distributions, shading and the frequency of UV care for 12 years were obtained. Subjective evaluation values were acquired as psychological features. As a result of CCA, it was found that the whole face can be made lighter in appearance by using UV protection every day continuously for six years or more.