Intrinsic Face Image Decomposition with Human Face Priors - Li, Chen; Zhou, Kun; Lin, Steve (European Conference on Computer Vision (ECCV), 2014)
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 approximate 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 constraints for intrinsic image estimation. These priors include statistics on skin reflectance 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 priors and a skin reflectance model for human faces, our method is able to achieve appreciable improvements in intrinsic image decomposition over more generic techniques.