Towards Sparse and Multiplexed Acquisition of Material BTFs

Abstract

We present preliminary results on our effort to combine sparse and illumination-multiplexed acquisition of bidirectional texture functions (BTFs) for material appearance. Both existing acquisition paradigms deal with a single specific problem: the desire to reduce either the number of images to be obtained while maintaining artifact-free renderings, or the shutter times required to capture the full dynamic range of a material's appearance. These problems have so far been solved by means of data-driven models. We demonstrate that the way these models are derived prevents combined sparse and multiplexed acquisition, and introduce a novel model that circumvents this obstruction. As a result, we achieve acquisition times on the order of minutes in comparison to the few hours required with sparse acquisition or multiplexed illumination.