Abstract

The Shape-from-Shading [SfS] problem infers shape from re- flected light, collected using a camera at a single point in space only. Reflected light alone does not provide sufficient constraint and extra information is required; typically a smoothness assumption is made. A surface with Lambertian reflectance lit by a single infinitely distant light source is also typical. We solve this typical SfS problem using belief propagation to marginalise a probabilistic model. The key novel step is in using a directional proba- bility distribution, the Fisher-Bingham distribution. This produces a fast and relatively simple algorithm that does an effective job of both extract- ing details and being robust to noise. Quantitative comparisons with past algorithms are provided using both synthetic and real data.