Title: Functional data analysis in the use of eyebrow shape as a biometric indicator in face recognition

Authors: A. Midori Albert; Cuixian Chen; Yishi Wang; Yaw Chang

Addresses: Department of Anthropology, University of North Carolina Wilmington, 601 South College Road, Wilmington, NC 28403-5907, USA ' Department of Mathematics and Statistics, University of North Carolina Wilmington, 601 South College Road, Wilmington, NC 28403, USA ' Department of Mathematics and Statistics, University of North Carolina Wilmington, 601 South College Road, Wilmington, NC 28403, USA ' Department of Mathematics and Statistics, University of North Carolina Wilmington, 601 South College Road, Wilmington, NC 28403, USA

Abstract: This paper reports the use of eyebrow shape as a point feature for face recognition in the identity sciences. An approach to quantifying eyebrow shape and results of an experiment to test how human perceptions of eyebrow shape (qualitative analyses) compare with quantitative analyses (i.e., computer generated algorithms) of eyebrow shape are discussed. The aim is to develop a method for face identification using a point feature, such as the eyebrow, in as much as face images used in forensic face image comparisons may be obscured due to sunglasses or head coverings, or indiscernible due to pose or lighting issues. Results showed that functional data analysis was successful in interpreting eyebrow shape from digitised face images, and that computer-classified (i.e., quantitative analyses) eyebrow shapes were more reliable than human perception (i.e., qualitative analyses) as a relatively high level of human subjectivity was evident from findings of a two-trial experiment on eyebrow classification.

Keywords: functional data analysis; face recognition; eyebrow shape; biometric indicators; identity sciences; point features; eyebrows; biometrics; eyebrow classification.

DOI: 10.1504/IJBM.2014.060980

International Journal of Biometrics, 2014 Vol.6 No.2, pp.166 - 179

Available online: 23 May 2014 *

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