A novel cognitive-psychology-based face-recognition system for improved identification rates for the problem of age-progression

Authors:
Karl Ricanek, Jr.;Ryan B. Wilkins;Amrutha Sethuram;Eric K. Patterson
Affiliations:
University of North Carolina Wilmington, Wilmington, NC;University of North Carolina Wilmington, Wilmington, NC;University of North Carolina Wilmington, Wilmington, NC;University of North Carolina Wilmington, Wilmington, NC
Venue:
VIIP '07 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing
Year:
2007

Citing 2
Cited 0

The FERET Evaluation Methodology for Face-Recognition Algorithms

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition

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Abstract

This paper discusses the novel application of an idea rooted in cognitive psychology to face recognition (FR). This cognitive-psychology method adapted for FR is evaluated against the difficult problem of age-progression. The age-progression problem occurs when enrolled images used by the FR algorithm are younger, typically more than one year in difference, than the test (probe) image. A model of a phenomenon in cognitive psychology known as "own-race bias" (ORB) is employed using Principle Components Analysis (PCA) as the face recognition engine. The ORB FR system has demonstrated performance gain of 200% over the baseline technique of Eigenfaces on the MORPH Album 2 face database. Where the baseline system Eigen face FR (which has been described in [1]) had a rank-based identification rate of 23%, the ORB-based FR achieved rates in the mid 50%.