Bayesian Relighting

Abstract

We present a simple method for relighting real objects viewed from a fixed camera position. Instead of setting up a calibrated measurement device, such as a light stage, we manually sweep a spotlight over the walls of a white room, illuminating the object indirectly. In contrast to previous methods, we use arbitrary and unknown angular distributions of incoming light. Neither the incident light nor the reflectance function need to be represented explicitly in our approach. The new method relies on images of a probe object, for instance a black snooker ball, placed near the target object. Pictures of the probe in a novel illumination are decomposed into a linear combination of measured images of the probe. Then, a linear combination of images of the target object with the same coefficients produces a synthetic image with the new illumination. We use a simple Bayesian approach to find the most plausible output image, given the picture of the probe and the statistics observed in the dataset of samples. Our results for a variety of novel illuminations, including synthetic lighting by relatively narrow light sources as well as natural illuminations, demonstrate that the new technique is a useful, low cost alternative to existing techniques for a broad range of objects and materials.