Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/349
Appears in Collections:Psychology Journal Articles
Peer Review Status: Refereed
Title: Face processing: human perception and principal components analysis
Authors: Hancock, Peter J B
Burton, A Mike
Bruce, Vicki
Keywords: PCA
Face recognition
Face texture
Face shape
Issue Date: 1996
Publisher: Psychonomic Society
Citation: Hancock PJB, Burton AM & Bruce V (1996) Face processing: human perception and principal components analysis, Memory and Cognition, 24 (1), pp. 26-40.
Abstract: Principal component analysis (PCA) of face images is here related to subjects' performance on the same images. In two experiments subjects were shown a set of faces and asked to rate them for distinctiveness. They were subsequently shown a superset of faces and asked to identify those which appeared originally. Replicating previous work, we found that hits and false positives (FPs) did not correlate: those faces easy to identify as being "seen" were unrelated to those faces easy to reject as being "unseen". PCA was performed on three data sets: (i) face images with eye-position standardised; (ii) face images morphed to a standard template to remove shape information; (iii) the shape information from faces only. Analyses based upon PCA of shape-free faces gave high predictions of FPs, while shape information itself contributed only to hits. Furthermore, while FPs were generally predictable from components early in the PCA, hits appear to be accounted for by later components. We conclude that shape and "texture" (the image-based information remaining after morphing) may be used separately by the human face processing system, and that PCA of images offers a useful tool for understanding this system.
Type: Journal Article
URI: http://hdl.handle.net/1893/349
DOI Link: http://dx.doi.org/10.3758/BF03197270
Rights: Published in Memory and cognition by Psychonomic Society
Affiliation: Psychology
University of Glasgow
Psychology

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