Inferring Reflectance under Real-world Illumination

Abstract

We address the problem of inferring homogeneous reflectance (BRDF) from a single image of a known shape in an unknown real-world lighting environment. With appropriate representations of lighting and reflectance, the image provides bilinear constraints on the two signals, and our task is to blindly isolate the latter. We achieve this by leveraging the statistics of real-world illumination and estimating the reflectance that is most likely under a distribution of probable illumination environments. Experimental results suggest that useable reflectance information can be often be inferred, and that these estimates are stable under changes in lighting.