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Poster Communications Year : 2013

Sparse BRDF Approximation using Compressive Sensing

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.
Nous expérimentons une méthode d'acquisition de BRDF à partir d'une image. Nous exprimons la BRDF dans une base de grande dimension et reconstruisons la brdf à l'aide du compressive sensing.
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Dates and versions

hal-00878049 , version 1 (29-10-2013)

Identifiers

  • HAL Id : hal-00878049 , version 1

Cite

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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