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Carnegie Mellon Robotics Institute

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Abstract

Face recognition has important applications in forensics (criminal identification) and security (biometric authentication). The problem of face recognition has been extensively studied in the computer vision community, from a variety of perspectives. A relatively new development is the use of facial asymmetry in face recognition, and we present here the results of a statistical investigation of this biometric. We first show how facial asymmetry informa- tion can be used to perform three different face recognition tasks--human identification (in the presence of expression variations), classification of faces by expression, and clas- sification of individuals according to sex. Initially, we use a simple classification method, and conduct a feature anal- ysis which shows the particular facial regions that play the dominant role in achieving these three entirely different clas- sification goals. We then pursue human identification under expression changes in greater depth, since this is the most important task from a practical point of view. Two different ways of improving the performance of the simple classifier are then discussed: (i) feature combinations and (ii) the use of resampling techniques (bagging and random subspaces). With these modifications, we succeed in obtaining near per- fect classification results on a database of 55 individuals, a statistically significant improvement over the initial results as seen by hypothesis tests of proportions.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Medical Robotics Technology Center

Associated Lab(s) / Group(s): Human Identification at a Distance, Computational Symmetry, Biomedical Image Analysis

Associated Project(s): Facial Asymmetry as a Biometric

Number of pages: 14

Text Reference

Sinjini Mitra, Nicole Lazar, and Yanxi Liu, "Understanding the Role of Facial Asymmetry in Human Face Identification," Statistics and Computing, Vol. 17January, 2007, pp. 57 - 70.

BibTeX Reference

@article{Mitra_2007_5579,
   author = "Sinjini Mitra, Nicole Lazar, and Yanxi Liu",
   journal = "Understanding the Role of Facial Asymmetry in Human Face Identification",
   booktitle = "Statistics and Computing",
   pages = "57 - 70",
   month = "January",
   year = "2007",
   volume = "17",
}

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