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BRDF Slices: Accurate Adaptive Anisotropic Appearance Acquisition

Jiri Filip, Radomir Vavra, Michal Haindl, Pavel Zid, Mikulas Krupika, Vlastimil Havran
CVPR 2013
doi:10.1109/CVPR.2013.193 /cvpr/2013/filip2013cvpr-brdf/

Abstract

In this paper we introduce unique publicly available dense anisotropic BRDF data measurements. We use this dense data as a reference for performance evaluation of the proposed BRDF sparse angular sampling and interpolation approach. The method is based on sampling of BRDF subspaces at fixed elevations by means of several adaptively-represented, uniformly distributed, perpendicular slices. Although this proposed method requires only a sparse sampling of material, the interpolation provides a very accurate reconstruction, visually and computationally comparable to densely measured reference. Due to the simple slices measurement and method's robustness it allows for a highly accurate acquisition of BRDFs. This in comparison with standard uniform angular sampling, is considerably faster yet uses far less samples.

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Text

Filip et al. "BRDF Slices: Accurate Adaptive Anisotropic Appearance Acquisition." Conference on Computer Vision and Pattern Recognition, 2013. doi:10.1109/CVPR.2013.193

Markdown

[Filip et al. "BRDF Slices: Accurate Adaptive Anisotropic Appearance Acquisition." Conference on Computer Vision and Pattern Recognition, 2013.](https://mlanthology.org/cvpr/2013/filip2013cvpr-brdf/) doi:10.1109/CVPR.2013.193

BibTeX

@inproceedings{filip2013cvpr-brdf,
  title     = {{BRDF Slices: Accurate Adaptive Anisotropic Appearance Acquisition}},
  author    = {Filip, Jiri and Vavra, Radomir and Haindl, Michal and Zid, Pavel and Krupika, Mikulas and Havran, Vlastimil},
  booktitle = {Conference on Computer Vision and Pattern Recognition},
  year      = {2013},
  doi       = {10.1109/CVPR.2013.193},
  url       = {https://mlanthology.org/cvpr/2013/filip2013cvpr-brdf/}
}