Race-related variation of facial features: Anthropometric data I

By A. G. Goldstein. 1979

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How We've Taught Algorithms to See Identity: Constructing Race and Gender in Image Databases for Facial Analysis (2020, background): “other features such as facial proportions are important [50, 54, 130, 131].”
Face Recognition (2018, unknown): “Humans may encode an \average" face; these averages may be di(cid:11)erent for di(cid:11)erent races, and recognition may su(cid:11)er from prejudice or unfamiliarity with the class of faces from another race [Goldstein, 1979b] or gender [Goldstein, 1979a].”
Culture Shapes How We Look at Faces (2008, background): “Both objective anthropometric measures [25,26] and computational models [19] have revealed comparable heterogeneity for Caucasian, African and East Asian faces.”
Thirty years of investigating the own-race bias in memory for faces: A meta-analytic review (2001, background): “Elliott, Wills, and Goldstein (1973) investigated the influence of paired”
The Other-Race Effect Develops During Infancy (2007, background): “However, the available evidence indicates that no category of faces has greater homogeneity than any other (Goldstein, 1979a, 1979b).”