Towards Sparse and Multiplexed Acquisition of Material BTFs

In proceedings of Eurographics Workshop on Material Appearance Modeling, 2017
 

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.

Bibtex

@INPROCEEDINGS{ddb-2017-sparse-multiplexed-acquisition,
     author = {den Brok, Dennis and Weinmann, Michael and Klein, Reinhard},
      title = {Towards Sparse and Multiplexed Acquisition of Material BTFs},
  booktitle = {Eurographics Workshop on Material Appearance Modeling},
       year = {2017},
   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.}
}