Extrapolating Large-Scale Material BTFs under Cross-Device Constraints

David Bommes, Tobias Ritschel, and Thomas Schultz (Editors)
In proceedings of Vision, Modeling & Visualization, pages 143-150, The Eurographics Association, 2015
 

Abstract

In this paper, we address the problem of acquiring bidirectional texture functions (BTFs) of large-scale material samples. Our approach fuses gonioreflectometric measurements of small samples with few constraint images taken on a flatbed scanner under semi-controlled conditions. Underlying our method is a lightweight texture synthesis scheme using a local texture descriptor that combines shading and albedo across devices. Since it operates directly on SVD-compressed BTF data, our method is computationally efficient and can be implemented on a moderate memory footprint.

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Bibtex

@INPROCEEDINGS{steinhausen2015crossdevice,
     author = {Steinhausen, Heinz Christian and den Brok, Dennis and Hullin, Matthias B. and Klein, Reinhard},
     editor = {Bommes, David and Ritschel, Tobias and Schultz, Thomas},
      pages = {143--150},
      title = {Extrapolating Large-Scale Material BTFs under Cross-Device Constraints},
  booktitle = {Vision, Modeling {\&} Visualization},
       year = {2015},
  publisher = {The Eurographics Association},
   abstract = {In this paper, we address the problem of acquiring bidirectional texture functions (BTFs) of
               large-scale material
               samples. Our approach fuses gonioreflectometric measurements of small samples with few constraint
               images taken
               on a flatbed scanner under semi-controlled conditions. Underlying our method is a lightweight
               texture synthesis
               scheme using a local texture descriptor that combines shading and albedo across devices. Since it
               operates directly
               on SVD-compressed BTF data, our method is computationally efficient and can be implemented on a
               moderate
               memory footprint.},
       isbn = {978-3-905674-95-8},
        doi = {10.2312/vmv.20151269}
}