Effecting an Improvement to the Fitness Function. How to Evolve a More Identifiable Face

Constructing the face of a criminal from the selection of individual facial parts is a hard task. We have been working on a new system called EvoFIT that involves the selection and breeding of complete faces. The approach is theoretically better founded and produces more identifiable composites than those from a traditional ‘feature’ system. In the current paper, we explored three new methods of presenting faces to a person using EvoFIT. A better quality face was evolved if (1) the external parts of the face were subjected to a Gaussian blur, allowing a user to focus on the important inner region of the face, (2) if the faces were simplified to make them sketch-like in appearance, and (3) if users took longer in deciding which faces to select for breeding. Taken together, these approaches would appear to make a marked improvement in the ability to evolve an identifiable likeness of a target.

• Type: Conference
• Year: 2008
• Where: BLISS
• Authors: Charlie D. Frowd, Joanne Park, Alex H. McIntyre, Vicki Bruce, Melanie Pitchford, Steve Fields, Mary Kenirons, Peter J. B. Hancock
• Keywords: Better Quality Face, BLISS 2008, Complete Faces, Individual Facial Parts, Machine Learning