Estimating facial albedo from a single image
This paper describes how a facial albedo map can be recovered from a single image using a statistical model that captures variations in surface normal direction. We fit the model to intensity data using constraints on the surface normal direction provided by Lambert's law and then use the differences between observed and reconstructed image brightness to estimate the albedo. We show that this process is stable under varying illumination. We then show how eigenfaces trained on albedo maps may provide a better representation for illumination insensitive recognition than those trained on raw image intensity.
albedo estimation shape-from-shading face recognition