Minimal image sets for robust spherical gradient photometric stereo

Abstract

State-of-the-art photometric shape and reflectance analysis uses polarized spherical gradient illumination images captured in a light stage. The quality of the estimated surface geometry degrades with interreflection, rotationally asymmetric reflectance lobes and light discretisation. We show that introducing additional parameters to model distortions in the diffuse reflectance lobe results in an underdetermined linear system. Results from existing approaches can be refined to satisfy this system using quadratic programming. We also describe how robust shape recovery can be achieved using a minimal four image set.