Analysis of human faces using a measurement-based skin reflectance model

We have measured 3D face geometry, skin reflectance, and subsur- face scattering using custom-built devices for 149 subjects of vary- ing age, gender, and race. We developed a novel skin reflectance model whose parameters can be estimated from measurements. The model decomposes the large amount of measured skin data into a spatially-varying analytic BRDF, a diffuse albedo map, and diffuse subsurface scattering. Our model is intuitive, physically plausible, and - since we do not use the original measured data - easy to edit as well. High-quality renderings come close to reproducing real photographs. The analysis of the model parameters for our sam- ple population reveals variations according to subject age, gender, skin type, and external factors (e.g., sweat, cold, or makeup). Using our statistics, a user can edit the overall appearance of a face (e.g., changing skin type and age) or change small-scale features using texture synthesis (e.g., adding moles and freckles). We are making the collected statistics publicly available to the research community for applications in face synthesis and analysis.