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To be presented at SIGGRAPHWe investigate the expressiveness of the microfacet model for isotropic BRDFs measured from real materials by introducing a non-parametric factor model that represents the model's functional structure but abandons restricted parametric formulations of its factors. We propose a new objective based on compressive weighting that controls rendering error in high dynamic range BRDF fits better than previous factorization approaches. We develop a simple numerical procedure to minimize this objective and handle dependencies that arise between microfacet factors. Our method faithfully captures a more comprehensive set of materials than previous state-of-the-art parametric approaches, yet remains compact (3.2KB per BRDF). We experimentally validate the benefit of the microfacet model over a naive orthogonal factorization, and show that fidelity for diffuse materials is modestly improved by fitting an unrestricted shadowing/masking factor. We also compare against a recent data-driven factorization approach [Bilgili et al. 2011] and show that our microfacet-based representation improves rendering accuracy for most materials while reducing storage by more than 10x. @article{ Bagher:2016:NPFMM, author = {Mahdi M. Bagher and John Snyder and Derek Nowrouzezahrai}, title = {A Non-Parametric Factor Microfacet Model for Isotropic BRDFs}, journal = {ACM Transactions on Graphics}, volume = {36}, number = {6}, year = {2016}, month = aug, } |