Surface estimation of translucent materials: an application to fabric digitization.

Abstract

Estimating the surface of translucent objects from photometric data poses significant challenges due to complex internal light scattering. We introduce a novel method that computes a depth map from single-viewpoint photographs of a material sample, captured under multiple illuminations. Our approach leverages inverse rendering to derive a volumetric representation, including density, albedo, and phase function, from which a surface mesh is reconstructed. Beyond validation with synthetic and 3D-printed physical models, we illustrate our technique's power by successfully applying it to the digitization of fabrics, a notoriously difficult material due to its intricate translucent structure. This work advances the state-of-the-art texture stack acquisition via enhanced surface reconstruction.