Face recognition in hyperspectral images

Authors:
Zhihong Pan;Glenn E. Healey;Manish Prasad;Bruce J. Tromberg
Affiliations:
Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, California;Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, California;Department of Electrical Engineering and Computer Science, University of California, Irvine, Irvine, California;Beckman Laser Institute, University of California, Irvine, Irvine, California
Venue:
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Year:
2003

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Abstract

Hyperspectral cameras provide useful discriminants for human face recognition that cannot be obtained by other imaging methods. We examine the utility of using nearinfrared hyperspectral images for the recognition of faces over a database of 200 subjects. The hyperspectral images were collected using a CCD camera equipped with a liquid crystal tunable filter. Spectral measurements over the near-infrared allow the sensing of subsurface tissue structure which is significantly different from person to person but relatively stable over time. The local spectral properties of human tissue are nearly invariant to face orientation and expression which allows hyperspectral discriminants to be used for recognition over a large range of poses and expressions. We describe a face recognition algorithm that exploits spectral measurements for multiple facial tissue types. We demonstrate experimentally that this algorithm can be used to recognize faces over time in the presence of changes in facial pose and expression.