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Sex classification is better with three-dimensional head structure than with image intensity information

MPG-Autoren
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Vetter,  T
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Troje,  NF
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

O'Toole, A., Vetter, T., Troje, N., & Bülthoff, H. (1997). Sex classification is better with three-dimensional head structure than with image intensity information. Perception, 26(1), 75-84. doi:10.1068/p260075.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-0013-EA7C-E
Zusammenfassung
The sex of a face is perhaps its most salient feature. 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.