Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/348
Appears in Collections:Psychology Journal Articles
Peer Review Status: Refereed
Title: Evolving faces from principal components
Authors: Hancock, Peter J B
Keywords: Face PCA
facial composites
Evolutionary algorithm
Eigenface
Eigenshape
Issue Date: Jun-2000
Publisher: Psychonomic Society
Citation: Hancock PJB (2000) Evolving faces from principal components, Behavior Research Methods, Instruments and Computers, 32 (2), pp. 327-333.
Abstract: A system that uses an underlying genetic algorithm to evolve faces in response to user selection is described. The descriptions of faces used by the system are derived from a statistical analysis of a set of faces. The faces used for generation are transformed to an average shape by defining locations around each face and morphing. The shape-free images and shape vectors are then separately subjected to principal components analysis. Novel faces are generated by recombining the image components ("eigenfaces") and then morphing their shape according to the principal components of the shape vectors ("eigenshapes"). The prototype system indicates that such statistical analysis of a set of faces can produce plausible, randomly generated photographic images.
Type: Journal Article
URI: http://hdl.handle.net/1893/348
DOI Link: http://dx.doi.org/10.3758/BF03207802
Rights: Published in Behavior research methods, instruments and computers by Psychonomic Society
Affiliation: Psychology

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