A Sampling Criterion for Optimizing a Surface Light Field

This paper adopts a sampling perspective to surface light field modeling. This perspective eliminates the need of using the actual object surface in the surface light field definition. Instead, the surface ought to provide only a parameterization of the surface light field function that specifically reduces aliasing artifacts visible at rendering. To find that surface, we propose a new criterion that aims at optimizing the smoothness of the angular distribution of the light rays emanating from each point on the surface. The main advantage of this approach is to be independent of any specific reflectance model. The proposed criterion is compared to widely used criteria found in multi-view stereo and its effectiveness is validated for modeling the appearance of objects having various unknown reflectance properties using calibrated images alone.