title: Evolving faces from principal components.
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 a statistical analysis of a set of faces can produce plausible, randomly generated photographic images.
authors.affiliation: Department of Psychology, University of Stirling, Scotland. pjbh1@stir.ac.uk
authors.forename: P J
authors.initials: PJ
authors.lastname: Hancock
mesh_terms: D005075:Biological Evolution; D003658:Decision Making, Computer-Assisted; D005145:Face / Q000033:anatomy & histology*; D005260:Female; D005554:Forensic Medicine / Q000379:methods*; D006801:Humans; D008445:Maxillofacial Development; D008957:Models, Genetic; D010364:Pattern Recognition, Visual