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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.

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Correspondence to Peter J. B. Hancock.

Additional information

This project was funded by EPSRC Grant GR/L88627. Bob Nicholls at the U.K. Home Office provided the original face images used.

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Hancock, P.J.B. Evolving faces from principal components. Behavior Research Methods, Instruments, & Computers 32, 327–333 (2000). https://doi.org/10.3758/BF03207802

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  • DOI: https://doi.org/10.3758/BF03207802

Keywords

  • Face Image
  • Target Face
  • User Selection
  • Ofthe Target
  • Shape Vector