Acquiring Bidirectional Texture Functions for Large-Scale Material Samples

In: Journal of WSCG (Juni 2014), 22:2(73-82)
 

Abstract

Most current acquisition setups for bidirectional texture functions (BTFs) are incapable of capturing large-scale material samples. We propose a method based on controlled texture synthesis to produce BTFs of appealing visual quality for such materials. Our approach uses as input data a complete measurement of a small fraction of the sample, together with few images of the large-scale structure controlling the synthesis process. We evaluate the applicability of our approach by reconstructing sparsified ground truth data and investigate the consequences of choosing different kinds and numbers of constraint images.

Stichwörter: bidirectional texture functions - texture synthesis - material appearance

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Bibtex

@ARTICLE{steinhausen2014,
    author = {Steinhausen, Heinz Christian and den Brok, Dennis and Hullin, Matthias B. and Klein, Reinhard},
     pages = {73--82},
     title = {Acquiring Bidirectional Texture Functions for Large-Scale Material Samples},
   journal = {Journal of WSCG},
    volume = {22},
    number = {2},
      year = {2014},
     month = jun,
  keywords = {bidirectional texture functions - texture synthesis - material appearance},
  abstract = {Most current acquisition setups for bidirectional texture functions (BTFs) are incapable of
              capturing large-scale material samples. We propose a method based on controlled texture synthesis to
              produce BTFs of appealing visual quality for such materials. Our approach uses as input data a
              complete measurement of a small fraction of the sample, together with few images of the large-scale
              structure controlling the synthesis process. We evaluate the applicability of our approach by
              reconstructing sparsified ground truth data and investigate the consequences of choosing different
              kinds and numbers of constraint images.}
}