Spectral reflectances of various parts of human faces from various ethnic races were measured as part of experiments on spectral imaging for human portraits. Principal components analysis (PCA) was applied to the spectral reflectances from the various races, and a variety of face parts. The first three principal components explain about 99.8% of cumulative contribution of variance of spectral reflectances for each race and each face part, and for all races as well. Color differences of spectral reconstruction either for individual races and all races or for individual face parts based on different sets of principal components were estimated. The results indicate that, when using three basis functions and under D50 illumination, the basis functions based only on spectra of Pacific–Asian subjects will provide the best overall color reproduction. However, from a spectral matching point of view, three basis functions based on all spectra will provide the best spectral reproduction with minimum overall mean value of metameric indices. More analyses were applied to spectral reflectances of human facial skin from different sources and their corresponding spectral reconstruction based on different sets of principal components. Those results provide practical suggestions for imaging, or spectral imaging, system design, especially imaging systems for human portraiture.
Qun Sun, Mark D. Fairchild, "Statistical Characterization of Face Spectral Reflectances and Its Application to Human Portraiture Spectral Estimation" in Journal of Imaging Science and Technology, 2002, pp 498 - 506, https://doi.org/10.2352/J.ImagingSci.Technol.2002.46.6.art00004