Facial Asymmetry Quantification for Expression Invariant Human Identification

Authors:
R. L. Weaver;K. L. Schmidt
Affiliations:
-;-
Venue:
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Year:
2002

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Cited 5

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Abstract

We investigate the effect of quantified statistical facial asymmetry as a biometric under expression variations. Our findings show that the facial asymmetry measures (AsymFaces) are computationally feasible, containing discriminative information and providing synergy when combined with Fisherface and Eigen-face methods on image data of two publically available face databases (Cohn-Kanade and Feret).