High-Res Facial Appearance Capture from Polarized Smartphone Images
We propose a novel method for high-quality facial texture reconstruction from
RGB images using a novel capturing routine based on a single smartphone which
we equip with an inexpensive polarization foil. Specifically, we turn the
flashlight into a polarized light source and add a polarization filter on top
of the camera. Leveraging this setup, we capture the face of a subject with
cross-polarized and parallel-polarized light. For each subject, we record two
short sequences in a dark environment under flash illumination with different
light polarization using the modified smartphone. Based on these observations,
we reconstruct an explicit surface mesh of the face using structure from
motion. We then exploit the camera and light co-location within a
differentiable renderer to optimize the facial textures using an
analysis-by-synthesis approach. Our method optimizes for high-resolution normal
textures, diffuse albedo, and specular albedo using a coarse-to-fine
optimization scheme. We show that the optimized textures can be used in a
standard rendering pipeline to synthesize high-quality photo-realistic 3D
digital humans in novel environments.