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Proceedings Paper

Robust face identification scheme: KL expansion of an invariant feature space
Author(s): Shigeru Akamatsu; Tsutomu Sasaki; Hideo Fukamachi; Yasuhito Suenaga
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Paper Abstract

This paper proposes a new approach for extracting features from face images that offer robust face identification against image variations. We combine the K-L expansion technique with two new operations that transform the face pattern into an invariant feature space. The two operations are the affine transformation which yields a standard face view from the input face image, and its transformation into the Fourier spectrum domain, which develops the property of shift-invariance. Although the basic idea of applying the K-L expansion to extract features for face recognition originates from the eigenface approach proposed by Turk and Pentland our scheme offers superior performance due to the transformation into the invariant feature space. The performance of the two schemes for face identification against various imaging conditions is compared.

Paper Details

Date Published: 1 February 1992
PDF: 14 pages
Proc. SPIE 1607, Intelligent Robots and Computer Vision X: Algorithms and Techniques, (1 February 1992); doi: 10.1117/12.57048
Show Author Affiliations
Shigeru Akamatsu, NTT Human Interface Labs. (Japan)
Tsutomu Sasaki, NTT Human Interface Labs. (Japan)
Hideo Fukamachi, NTT Software Corp. (Japan)
Yasuhito Suenaga, NTT Human Interface Labs. (Japan)


Published in SPIE Proceedings Vol. 1607:
Intelligent Robots and Computer Vision X: Algorithms and Techniques
David P. Casasent, Editor(s)

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