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Proceedings Paper

Hyperspectral face recognition under variable outdoor illumination
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Paper Abstract

We examine the performance of illumination-invariant face recognition in outdoor hyperspectral images using a database of 200 subjects. The hyperspectral camera acquires 31 bands over the 700-1000nm spectral range. Faces are represented by local spectral information for several tissue types. Illumination variation is modeled by low-dimensional spectral radiance subspaces. Invariant subspace projection over multiple tissue types is used for recognition. The experiments consider various face orientations and expressions. The analysis includes experiments for images synthesized using face reflectance images of 200 subjects and a database of over 7,000 outdoor illumination spectra. We also consider experiments that use a set of face images that were acquired under outdoor illumination conditions.

Paper Details

Date Published: 12 August 2004
PDF: 10 pages
Proc. SPIE 5425, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X, (12 August 2004); doi: 10.1117/12.543102
Show Author Affiliations
Zhihong Pan, Univ. of California/Irvine (United States)
Glenn E. Healey, Univ. of California/Irvine (United States)
Manish Prasad, Univ. of California/Irvine (United States)
Bruce J. Tromberg, Univ. of California/Irvine (United States)


Published in SPIE Proceedings Vol. 5425:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery X
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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