20 August 2001 Models for recognizing faces in hyperspectral images
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Abstract
Hyperspectral sensors provide useful discriminant for human face identification that cannot be obtained by other sensing modalities. The spectral properties of human tissue vary significantly from person to person. While the visible spectral characteristics of a person's skin may change over time, near-infrared spectral measurements allow the sensing of subsurface tissue change over time, near-infrared spectral measurements allow the sensing of subsurface tissue structure that is difficult for a subject to modify. The high spectral dimensionality of hyper-spectral imagery provides the opportunity to recognize subpixel features which enables reliable identification at large distances. We propose methods for the identification of humans using properties of individual tissue types as well as combinations of tissue types. Intrinsic models for facial tissue types for a person can be constructed form a single hyperspectral image. These models can be used to generate spectral subspaces that model the set of spectra for a face over a range of facial orientations, environmental conditions, and spectral mixtures.
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Glenn Healey, Glenn Healey, Zhihong Pan, Zhihong Pan, Bruce J. Tromberg, Bruce J. Tromberg, } "Models for recognizing faces in hyperspectral images", Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); doi: 10.1117/12.437022; https://doi.org/10.1117/12.437022
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