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Journal of Electronic Imaging

Face authentication using a hybrid approach
Author(s): Vitomir Štruc; F. Mihelic; N. Pavesic
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Paper Abstract

We present a hybrid approach to face feature extraction based on the trace transform and the novel kernel partial leastsquares discriminant analysis (KPA). The hybrid approach, called trace kernel partial least-squares discriminant analysis (TKPA), first uses a set of 15 trace functionals to derive robust and discriminative facial features and then applies the KPA method to reduce their dimensionality. The feasibility of the proposed approach was successfully tested on the XM2VTS database, where a false rejection rate (FRR) of 1.25% and a false acceptance rate (FAR) of 2.11% were achieved in our best-performing face authentication experiment. The experimental results also show that the proposed approach can outperform kernel methods such as generalized discriminant analysis (GDA), kernel Fisher analysis (KFA), and complete kernel Fisher discriminant analysis (CKFA) as well as combinations of these methods with features extracted using the trace transform.

Paper Details

Date Published: 1 January 2008
PDF: 11 pages
J. Electron. Imaging. 17(1) 011003 doi: 10.1117/1.2885149
Published in: Journal of Electronic Imaging Volume 17, Issue 1
Show Author Affiliations
Vitomir Štruc, Univ. v Ljubljani (Slovenia)
F. Mihelic, Univ. v Ljubljani (Slovenia)
N. Pavesic, Univ. v Ljubljani (Slovenia)


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