Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce a novel fitting procedure that takes as input an arbitrary material, possibly anisotropic, and automatically converts it to a microfacet BRDF. Our algorithm is based on the property that the distribution of microfacets may be retrieved by solving an eigenvector problem that is built solely from backscattering samples.  show that the eigenvector associated to the largest eigenvalue is always the only solution to this problem, and compute it using the por iteration method. This approach is straightforward to implement, much faster to compute, and considerably more robust than solutions based on nonlinear optimizations. In addition,  provide simple conversion procedures of our fits into both Beckmann and GGX roughness parameters, and discuss the advantages of microfacet slope space to make our fits editable.  apply our method to measured materials from two large databases that include anisotropic materials, and demonstrate the benefits of spatially varying roughness on texture mapped geometric models.
['Jonathan Dupuy', 'Eric Heitz', 'Jean Claude Iehl', 'Pierre Poulin', 'Victor Ostromoukhov']
I am writing a research paper on a idea Extracting Microfacet-based BRDF Parameters from Arbitrary Materials with Power Iterations
[{"from": "human", "value": "I am writing a research paper on a idea Extracting Microfacet-based BRDF Parameters from Arbitrary Materials with Power Iterations"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce a novel fitting procedure that takes as input an arbitrary material, possibly anisotropic, and automatically converts it to a microfacet BRDF. Our algorithm is based on the property that the distribution of microfacets may be retrieved by solving an eigenvector problem that is built solely from backscattering samples.  show that the eigenvector associated to the largest eigenvalue is always the only solution to this problem, and compute it using the por iteration method. This approach is straightforward to implement, much faster to compute, and considerably more robust than solutions based on nonlinear optimizations. In addition,  provide simple conversion procedures of our fits into both Beckmann and GGX roughness parameters, and discuss the advantages of microfacet slope space to make our fits editable.  apply our method to measured materials from two large databases that include anisotropic materials, and demonstrate the benefits of spatially varying roughness on texture mapped geometric models."}]