Speaker: Saip-Can Hasbay
Abstract
The lack of a universal material representation remains a significant challenge in appearance modeling, limiting the standardization of Bidirectional Scattering Distribution Functions (BSDFs).
In this thesis, we unify various material representations under SAPO distribution. To cope with challenging multimodal data commonly encountered in appearance modeling, we introduce SAPO mixture models.We obtain the multivariate representation via marginal-conditional SAPO and show that interpolation leads to a feasible continuous representation.
Alongside their flexibility in representing various families of distributions, SAPO offer intuitive parameters, exceptional compression, and differentiability. Furthermore, their ease of use and closed-form analytical formulation make them a natural choice for simulation applications. Given these properties, we introduce SAPO BSDFs as a unified representation for appearance modeling. We demonstrate that SAPO BSDFs accurately reproduce both established analytic models and data-driven BSDFs, effectively establishing the Fellowship of SAPO BSDFs.
