Abstract

We present a method for decomposing a single face photograph into its intrinsic image components. Intrinsic image decomposition has commonly been used to facilitate image editing operations such as relighting and re-texturing. Although current single-image intrinsic image methods are able to obtain an ap- proximate decomposition, image operations involving the human face require greater accuracy since slight errors can lead to visually disturbing results. To improve decomposition for faces, we propose to utilize human face priors as con- straints for intrinsic image estimation. These priors include statistics on skin re- flectance and facial geometry. We also make use of a physically-based model of skin translucency to heighten accuracy, as well as to further decompose the reflectance image into a diffuse and a specular component. With the use of pri- ors and a skin reflectance model for human faces, our method is able to achieve appreciable improvements in intrinsic image decomposition over more generic techniques.