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 leverag- ing the statistics of real-world illumination and estimating the reflectance that is most likely under a distribution of probable illumination environ- ments. Experimental results with a variety of real and synthetic images suggest that useable reflectance information can be inferred in many cases, and that these estimates are stable under changes in lighting.