Visible skin color distribution plays a role in the perception of age, attractiveness, and health in female faces☆

Discrimination of Attractiveness and Health in Men’s Faces: the Impact of Color Cues and Variation in Relation to Sex and Age of Rater

“…The significant Image type x Quality x Color condition interaction suggests that higher scores are awarded to high quality individuals compared with low quality individuals when presented in the color condition than in monochrome, but only for the skin images. Our results are consistent with recent findings that skin color and the distribution of skin coloration are important in judgements of mate quality (Fink et al 2001(Fink et al , 2006Jones et al 2004a, b;Stephen et al 2009). Color information is not the only cue to quality, however, since high quality individuals received higher scores than low quality individuals, even when judged in monochrome, in both face and skin image presentations.…”

“…Consistent with this idea, skin condition accurately predicts overall facial attractiveness independently of information about facial shape (Jones et al 2004a, b;Fink et al 2006;Fink and Matts 2008). Furthermore, perceived health of facial skin patches cropped from the cheek area of digital images positively correlate with ratings of the attractiveness of men's faces (Jones et al 2004a), and men with relatively symmetric faces were perceived as having healthier facial skin than those with asymmetric faces (Jones et al 2004b).…”

“…Furthermore, relating color attributes to attractiveness ratings, Fink et al (2001) found that attractiveness was negatively correlated with variability in blue color space in women's faces, but was also predicted by homogeneity of contrast, suggesting that both color and textural cues influence judgments. In subsequent studies, Fink and colleagues showed that both homogeneity of skin color distribution and skin surface topography predicts perception of attractiveness, age and health in women's (Fink et al 2006;Fink and Matts 2008) and men's faces (Fink et al 2012).…”

A Novel Framework for Assessing Facial Attractiveness Based on Facial Proportions

“…O'Toole et al [28] calculated average face shapes and textures based on 3D scan data of 200 men and women, and proved that averageness influences attractiveness in 3D faces, just as in 2D faces. Fink et al [29] revealed that skin texture has a considerable influence on the attractiveness evaluation of 3D faces by constructing a skin map with various skin colors that is fitted to a 3D face template to normalize face shape. Jang et al [30] estimated facial attractiveness through manually detected landmarks on a 3D face, and calculated the height of the nose, the horizontal and vertical curvatures of the forehead, the curvature of the cheek, and the chin volume.…”

An Own-Age Bias in Young Adults' Facial Age Judgments

“…The majority of studies on adults' facial age judgments have focused on accuracy in judging facial age, which have shown that adults are generally accurate in judging the age of own-race faces (Burt & Perrett, 1995;George & Hole, 1995Henss, 1991). Other studies have also focused on the different facial cues that adults use to judge age, such as craniofacial shape, amount of cranial hair, presence or absence of wrinkles, appearance and height of internal facial features, and skin tone (Burt & Perrett, 1995;Fink, Grammer, & Matts, 2006;George & Hole, 1995, 1998Gross, 1997;Mark et al, 1980;Pittenger & Shaw, 1975;Wogalter & Hosie, 1991).…”