Sex classification is better with three-dimensional head structure than with image intensity information.
The sex of a face is perhaps its most salient features. A principal components analysis (PCA) was applied separately to the three-dimensional (3-D) structure and graylevel image (GLI) data from laser-scanned human heads. Individual components from both analyses captured information related to the sex of the face. Notably, single projection coefficients characterized complex differences between the 3-D structure of male and female heads and between male and female GLI maps. In a series of simulations, the quality of the information available in the 3-D head versus GLI data for predicting the sex of the face has been compared. The results indicated that the 3-D head data supported more accurate sex classification than the GLI data, across a range of PCA-compressed (dimensionality-reduced) representations of the heads. This kind of dual face representation can give insight into the nature of the information available to humans for categorizing and remembering faces.
O'Toole
A J
AJ
School of Human Development, University of Texas at Dallas, Richardson 75083-0688, USA. otoole@utdallas.edu
Vetter
T
T
Troje
N F
NF
Bülthoff
H H
HH
D000328:Adult; D003198:Computer Simulation; D015350:Contrast Sensitivity; D005260:Female; D005556:Form Perception; D006257:Head / Q000033:anatomy & histology*; D006801:Humans; D008297:Male; D008953:Models, Anatomic; D012727:Sex Characteristics