Sparse BRDF Approximation using Compressive Sensing

Benoît Zupancic 1 Cyril Soler 1
1 MAVERICK - Models and Algorithms for Visualization and Rendering
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : We experiment a BRDF acquisiton method from a single picture, knowing geometry and illumination. To tackle such a severely underconstrained problem, we express the BRDF in a high dimensional basis, and perform the reconstruction using compressive sensing, looking for the most sparse solution to the linear problem of fitting the measurement image.
Document type :
Poster communications
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Contributor : Benoît Zupancic <>
Submitted on : Tuesday, October 29, 2013 - 3:44:30 PM
Last modification on : Wednesday, April 11, 2018 - 1:59:30 AM
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  • HAL Id : hal-00878049, version 1



Benoît Zupancic, Cyril Soler. Sparse BRDF Approximation using Compressive Sensing. 6th Siggraph Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia, Nov 2013, Hong-Kong, Hong Kong SAR China. ⟨hal-00878049⟩



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