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Proceedings Paper

Expression-invariant multispectral face recognition: you can smile now!
Author(s): Ioannis A. Kakadiaris; George Passalis; George Toderici; Yunliang Lu; Nikos Karampatziakis; Najam Murtuza; Theoharis Theoharis
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Paper Abstract

Face recognition performance has always been affected by the different facial expressions a subject may display. In this paper, we present an extension to the UR3D face recognition algorithm, which enables us to decrease the discrepancy in its performance for datasets from subjects with and without a neutral facial expression, from 15% to 3%.

Paper Details

Date Published: 17 April 2006
PDF: 7 pages
Proc. SPIE 6202, Biometric Technology for Human Identification III, 620204 (17 April 2006); doi: 10.1117/12.665697
Show Author Affiliations
Ioannis A. Kakadiaris, Univ. of Houston (United States)
George Passalis, Univ. of Houston (United States)
George Toderici, Univ. of Houston (United States)
Yunliang Lu, Univ. of Houston (United States)
Nikos Karampatziakis, Univ. of Houston (United States)
Najam Murtuza, Univ. of Houston (United States)
Theoharis Theoharis, Univ. of Houston (United States)


Published in SPIE Proceedings Vol. 6202:
Biometric Technology for Human Identification III
Patrick J. Flynn; Sharath Pankanti, Editor(s)

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