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

Functional data analysis in the use of eyebrow shape as a biometric indicator in face recognition 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Biometrics Inderscience Publishers

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

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1755-8301
eISSN
1755-831X
DOI
10.1504/IJBM.2014.060980
Publisher site
See Article on Publisher Site

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.

Journal

International Journal of BiometricsInderscience Publishers

Published: Jan 1, 2014

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