Perceptually validated analytical BRDFs parameters remapping

Abstract

The need to manually match the appearance of a material in two or more different rendering tools is common in digital 3D product design, due to the wide range of tools and material models commonly used, and a lack of standards to exchange materials data. Since the effect of BRDF parameters on rendered images is non-uniform, visually matching to a reference is time consuming and error-prone. We present an automatic BRDF remapping technique to match the appearance of a source material model to a target, providing a mapping between their parameter spaces. Our framework, based on Genetic Algorithm optimization and an image space similarity metric, provides a faithful mapping among analytical BRDFs, even when the BRDF models are deeply different. Objective and perceptual evaluations confirm the efficacy of the framework.