Illumination Face Spaces Are Idiosyncratic.
Jen-Mei Chang, J. Ross Beveridge, Bruce A. Draper, Michael J. L. Kirby, Holger P. Kley, Chris Peterson · 2006
Illumination spaces capture how the appearances of human faces vary under changing illumination. This work models illumination spaces as points on a Grassmann manifold and uses distance measures on this manifold to show that every person in the CMU-PIE and Yale data sets has a unique and identifying illumination space. This suggests that variations under changes in illumination can be exploited for their discriminatory information. As an example, when face recognition is cast as matching sets of face images to sets of face images, subjects in the CMU-PIE and Yale databases can be recognized with 100 % accuracy. 1.