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Classifying adults' and children's faces by sex: computational investigations of subcategorical feature
 

Summary: Classifying adults' and children's faces by sex:
computational investigations of subcategorical feature
encoding
Yi D. Cheng, Alice J. O'Toole*, Herve´ Abdi
The University of Texas at Dallas, School of Human Development, GR 4.1, Cognition & Neuroscience
Program, Richardson, TX 75083-0688, USA
Abstract
The faces of both adults and children can be classified accurately by sex, even in the absence
of sex-stereotyped social cues such as hair and clothing (Wild et al., 2000). Although much is known
from psychological and computational studies about the information that supports sex classification
for adults' faces, children's faces have been much less studied. The purpose of the present study was
to quantify and compare the information available in adults' versus children's faces for sex classifi-
cation and to test alternative theories of how human observers distinguish male and female faces for
these different age groups. We implemented four computational/neural network models of this task
that differed in terms of the age categories from which the sex classification features were derived.
Two of the four strategies replicated the advantage for classifying adults' faces found in previous
work. To determine which of these strategies was a better model of human performance, we compared
the performance of the two models with that of human subjects at the level of individual faces. The
results suggest that humans judge the sex of adults' and children's faces using feature sets derived
from the appropriate face age category, rather than applying features derived from another age

  

Source: Abdi, Hervé - School of Behavioral and Brain Sciences, University of Texas at Dallas

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences