Designing metrics for the purpose of aesthetically evaluating images

  • Authors:
  • Gary Greenfield

  • Affiliations:
  • Mathematics and Computer Science, University of Richmond, Richmond, Virginia

  • Venue:
  • Computational Aesthetics'05 Proceedings of the First Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
  • Year:
  • 2005

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Abstract

The algorithmic and evolutionary art movements within computer-generated art have helped spur interest in evaluating images on the basis of their aesthetic merit. When attempting to use non-interactive techniques to address this issue, two problems arise: (1) designing metrics that have explicit computational representations, and (2) establishing that such metrics actually fulfill their intended purpose. We survey our experiences in designing metrics for non-interactively guiding image evolution to obtain aesthetic images and we propose a taxonomy for metric frameworks. We also discuss some issues relevant to validating such metrics.