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01.01.2011 | Focus

Evolving the face of a criminal: how to search a face space more effectively

verfasst von: Charlie Frowd, Vicki Bruce, Melanie Pitchford, Carol Gannon, Mark Robinson, Colin Tredoux, Jo Park, Alex Mcintyre, Peter J. B. Hancock

Erschienen in: Soft Computing | Ausgabe 1/2011

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Abstract

Witnesses and victims of serious crime are often required to construct a facial composite, a visual likeness of a suspect’s face. The traditional method is for them to select individual facial features to build a face, but often these images are of poor quality. We have developed a new method whereby witnesses repeatedly select instances from an array of complete faces and a composite is evolved over time by searching a face model built using PCA. While past research suggests that the new approach is superior, performance is far from ideal. In the current research, face models are built which match a witness’s description of a target. It is found that such ‘tailored’ models promote better quality composites, presumably due to a more effective search, and also that smaller models may be even better. The work has implications for researchers who are using statistical modelling techniques for recognising faces.

Vorheriger Artikel A mixed integer genetic algorithm used in biological and chemical defense applications

Nächster Artikel Genetic programming of the stochastic interpolation framework: convection–diffusion equation

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Titel: Evolving the face of a criminal: how to search a face space more effectively
verfasst von: Charlie Frowd
Vicki Bruce
Melanie Pitchford
Carol Gannon
Mark Robinson
Colin Tredoux
Jo Park
Alex Mcintyre
Peter J. B. Hancock
Publikationsdatum: 01.01.2011
Verlag: Springer-Verlag
Erschienen in: Soft Computing / Ausgabe 1/2011
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-009-0518-x

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