Facial Asymmetry: A New Biometric

Yanxi Liu, R.L. Weaver, Karen Schmidt, N. Serban, and Jeffrey Cohn
tech. report CMU-RI-TR-01-23, Robotics Institute, Carnegie Mellon University, August, 2001


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Abstract
Human facial asymmetry has long been a critical factor for evaluations of attractiveness and expressions in psychology and anthropology, although most studies are carried out qualitatively. In this work, we investigate in depth the effect of statistical facial asymmetry measurement as a biometric under expression variations. Our findings demonstrate that the asymmetry of specific facial regions captures individual differences that are robust to variation in facial expression. More importantly, our experimental results show that facial asymmetry provides discriminating power orthogonal to conventional face identification methods. The synergy of combining facial asymmetry with conventional methods is evaluated. Our work appears to be the first to show quantitatively the power of facial asymmetry as a biometric.

Keywords
facial asymmetry, expression, face identification, feature selection

Notes
Grant ID: ONR N00014-00-1-0915 (HumanID)
Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Medical Robotics Technology Center
Associated Lab(s) / Group(s): Human Identification at a Distance, Face Group, Computational Symmetry, Component Analysis, Biomedical Image Analysis
Associated Project(s): Facial Asymmetry as a Biometric and Face Recognition

Text Reference
Yanxi Liu, R.L. Weaver, Karen Schmidt, N. Serban, and Jeffrey Cohn, "Facial Asymmetry: A New Biometric," tech. report CMU-RI-TR-01-23, Robotics Institute, Carnegie Mellon University, August, 2001

BibTeX Reference
@techreport{Liu_2001_3771,
   author = "Yanxi Liu and R.L. Weaver and Karen Schmidt and N. Serban and Jeffrey Cohn",
   title = "Facial Asymmetry: A New Biometric",
   booktitle = "",
   institution = "Robotics Institute",
   month = "August",
   year = "2001",
   number= "CMU-RI-TR-01-23",
   address= "Pittsburgh, PA",
}