Face recognition in hyperspectral images

Hyperspectral cameras provide useful discriminants for human face recognition that cannot be obtained by other imaging methods. We examine the utility of using near-infrared hyperspectral images for the recognition of faces over a database of 200 subjects. The hyperspectral images were collected usi...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2003-12, Vol.25 (12), p.1552-1560
Main Authors: Zhihong Pan, Healey, G., Prasad, M., Tromberg, B.
Format: Article
Language:English
Subjects:
Algorithms
Charge coupled devices
Charge-coupled image sensors
Face
Face recognition
Facial
Filters
Humans
Hyperspectral imaging
Hyperspectral sensors
Image databases
Image recognition
Invariants
Liquid crystals
Recognition
Spectra
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Summary:Hyperspectral cameras provide useful discriminants for human face recognition that cannot be obtained by other imaging methods. We examine the utility of using near-infrared 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 to provide 31 bands over the near-infrared (0.7 /spl mu/m-1.0 /spl mu/m). 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.
ISSN:0162-8828
1939-3539
DOI:10.1109/TPAMI.2003.1251148