  While the problem of estimating shapes and diffuse reflectances of human
faces from images has been extensively studied, there is relatively less work
done on recovering the specular albedo. This paper presents a lightweight
solution for inferring photorealistic facial reflectance and geometry. Our
system processes video streams from two views of a subject, and outputs two
reflectance maps for diffuse and specular albedos, as well as a vector map of
surface normals. A model-based optimization approach is used, consisting of the
three stages of multi-view face model fitting, facial reflectance inference and
facial geometry refinement. Our approach is based on a novel formulation built
upon the 3D morphable model (3DMM) for representing 3D textured faces in
conjunction with the Blinn-Phong reflection model. It has the advantage of
requiring only a simple setup with two video streams, and is able to exploit
the interaction between the diffuse and specular reflections across multiple
views as well as time frames. As a result, the method is able to reliably
recover high-fidelity facial reflectance and geometry, which facilitates
various applications such as generating photorealistic facial images under new
viewpoints or illumination conditions.
