title: Face-space architectures: evidence for the use of independent color-based features.
abstract: The concept of psychological face space lies at the core of many theories of face recognition and representation. To date, much of the understanding of face space has been based on principal component analysis (PCA); the structure of the psychological space is thought to reflect some important aspects of a physical face space characterized by PCA applications to face images. In the present experiments, we investigated alternative accounts of face space and found that independent component analysis provided the best fit to human judgments of face similarity and identification. Thus, our results challenge an influential approach to the study of human face space and provide evidence for the role of statistically independent features in face encoding. In addition, our findings support the use of color information in the representation of facial identity, and we thus argue for the inclusion of such information in theoretical and computational constructs of face space.
authors.affiliation: Center for the Neural Basis of Cognition and Department of Psychology, Carnegie Mellon University, 4400 Fifth Ave., Pittsburgh, PA, 15213-3890, USA. anestor@andrew.cmu.edu
authors.forename: Adrian
authors.initials: A
authors.lastname: Nestor
authors.forename: David C
authors.initials: DC
authors.lastname: Plaut
authors.forename: Marlene
authors.initials: M
authors.lastname: Behrmann
mesh_terms: D000328:Adult; D003118:Color Perception / Q000502:physiology*; D003198:Computer Simulation; D005145:Face; D005260:Female; D006801:Humans; D008297:Male; D008960:Models, Psychological; D025341:Principal Component Analysis; D014796:Visual Perception / Q000502:physiology*; D055815:Young Adult
keywords: color perception; computer simulation; face perception; face recognition; face space; facial features; independent component analysis; principal component analysis