@inproceedings{e5893f1d84614d689196dc11633d35fd,
title = "Facial asymmetry quantification for expression invariant human identification",
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)).",
author = "Y. Liu and Schmidt, {K. L.} and Cohn, {J. F.} and Weaver, {R. L.}",
note = "Funding Information: The authors thank Professor Andrew Moore, Drs. Geoff Gordon and Tom Minka of CMU, and J. Phillips of DARPA for productive discussions. CMU students R.L. Weaver (statistics), Dan Bohus (computer science), Marc Fasnacht (physics), Yan Karklin (computer science), and N. Serban (statistics) worked with Dr. Liu on subsets of the data reported here for course projects (Fall 2000, Spring 2001). Jiayong Zhang generated Fig. 13 . This research is supported in part by ONR N00014-00-1-0915 (HumanID), by NSF Grant IIS-0099597 and by NIMH Grant MH-51435. ; 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002 ; Conference date: 20-05-2002 Through 21-05-2002",
year = "2002",
doi = "10.1109/AFGR.2002.1004156",
language = "English (US)",
isbn = "0769516025",
series = "Proceedings - 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002",
publisher = "IEEE Computer Society",
pages = "208--214",
booktitle = "Proceedings - 5th IEEE International Conference on Automatic Face Gesture Recognition, FGR 2002",
address = "United States",
}