Facial asymmetry quantification for expression invariant human identification

Y. Liu, K. L. Schmidt, J. F. Cohn, R. L. Weaver

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Scopus citations

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 (T. Kanade et al., 1999) and Feret (P.J. Phillips et al., 1998)).

Original languageEnglish (US)
Title of host publicationProceedings - 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002
PublisherIEEE Computer Society
Pages208-214
Number of pages7
ISBN (Print)0769516025, 9780769516028
DOIs
StatePublished - Jan 1 2002
Event5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002 - Washington, DC, United States
Duration: May 20 2002May 21 2002

Publication series

NameProceedings - 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002

Other

Other5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002
CountryUnited States
CityWashington, DC
Period5/20/025/21/02

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All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Cite this

Liu, Y., Schmidt, K. L., Cohn, J. F., & Weaver, R. L. (2002). Facial asymmetry quantification for expression invariant human identification. In Proceedings - 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002 (pp. 208-214). [1004156] (Proceedings - 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002). IEEE Computer Society. https://doi.org/10.1109/AFGR.2002.1004156