Reflectance Capture Using Univariate Sampling of BRDFs

Zhuo Hui, Kalyan Sunkavalli, Joon-Young Lee, Sunil Hadap, Jian Wang, Aswin C. Sankaranarayanan; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017, pp. 5362-5370

Abstract


We propose the use of a light-weight setup consisting of a collocated camera and light source --- commonly found on mobile devices --- to reconstruct surface normals and spatially-varying BRDFs of near-planar material samples. A collocated setup provides only a 1-D "univariate" sampling of the 4-D BRDF. We show that a univariate sampling is sufficient to estimate parameters of commonly used analytical BRDF models. Subsequently, we use a dictionary-based reflectance prior to derive a robust technique for per-pixel normal and BRDF estimation. We demonstrate real-world shape and capture, and its application to material editing and classification, using real data acquired using a mobile phone.

Related Material


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[bibtex]
@InProceedings{Hui_2017_ICCV,
author = {Hui, Zhuo and Sunkavalli, Kalyan and Lee, Joon-Young and Hadap, Sunil and Wang, Jian and Sankaranarayanan, Aswin C.},
title = {Reflectance Capture Using Univariate Sampling of BRDFs},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV)},
month = {Oct},
year = {2017}
}