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RI | Publications | Human Identification versus Expression Classification via Bagging on Facial Asymmetry
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Text only version of this site
Human Identification versus Expression Classification via Bagging on Facial Asymmetry
Y. Liu and S. Mitra
tech. report CMU-RI-TR-03-08, Robotics Institute, Carnegie Mellon University, April, 2003.
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| Abstract |
We demonstrate a dual usage of quantified facial asymmetry for (1) human identification under expression variations and (2) expression classification across different human subjects. Our experiments show the effectiveness of using statistical bagging and feature subspace selection BEFORE applying classiffers such as Linear Discriminant Analysis. This preprocessing allows the same type but different dimensions of image features to be discriminative for two seemingly conflicting classiffcation goals. Statistically significant improvements are found when facial asymmetry features are combined into classical classifiers.
| Notes |
Associated centers: VASC and MRTC
Associated labs/groups: Human Identification at a Distance, Biomedical Image Analysis, Face Group, Human Sensing, and Computational Symmetry
Associated project: Facial Asymmetry as a Biometric
| Text Reference |
Y. Liu and S. Mitra, Human Identification versus Expression Classification via Bagging on Facial Asymmetry, tech. report CMU-RI-TR-03-08, Robotics Institute, Carnegie Mellon University, April, 2003.
| BibTeX Reference |
@techreport{Liu_2003_4366,
author = "Yanxi Liu and S. Mitra",
title = "Human Identification versus Expression Classification via Bagging on Facial Asymmetry",
institution = "Robotics Institute, Carnegie Mellon University",
month = "April",
year = "2003",
number = "CMU-RI-TR-03-08",
address = "Pittsburgh, PA"
}