![]() We focus on isotropic BRDFs and propose a new separable BRDF representation inspired by the projected deviation vector (PDV) parameterization described by Löw et al. In this paper, we set out to address these challenges by developing a new class of separable data-driven BRDF models which allow for compact representations of BRDFs in a low-dimensional space. It is, therefore, necessary to further develop compact representations which allow for detailed representations of the reflectance distributions with minimal approximation errors. Second, measured data are difficult to edit, analyze, and in other ways interact with. First, although significant progress has been made,, accurate BRDF and SvBRDF measurements are still challenging due to mechanical and computational complexity. ![]() There are, however, still a number of important challenges that need to be solved in order to make data-driven models flexible and easy to use in practice. The advantage of data-driven approaches is that carefully measured BRDFs automatically bring the detailed appearance of real-world materials into rendering pipeline. Recently, measured materials and appearance capture techniques have gained significant popularity, for an overview see. This has led to the development of both accurate parametric models, and advanced data-driven methods for describing, measuring and analyzing for virtually all classes of materials. The accuracy in the simulation of scattering at surfaces and computation of the light transport in a scene is determined by the way the material properties such as color and reflectance, modeled by the Bidirectional Reflectance Distribution Function (BRDF), are measured and represented. Over the last decade, we have seen the development of computer graphics algorithms and techniques which enable the quality and accuracy needed to make rendered images truly comparable to photographs of the same scene. To demonstrate the benefit of the proposed factored models, we present a new Monte Carlo importance sampling scheme and give examples of how they can be used for efficient BRDF capture and intuitive editing of measured materials. ![]() We evaluate the models using different parameterizations with different characteristics and show that both the BRDF data itself and the resulting renderings yield more accurate results in terms of both numerical errors and visual results compared to previous approaches. The proposed 3D and 2D BRDF representations can be factored into three or two 1D factors, respectively, while accurately representing the underlying BRDF data with only small approximation error. ![]() This paper presents two new data-driven BRDF models specifically designed for 1D separability. There are, however, a number of key challenges that need to be solved in order to enable efficient capture, representation and interaction with real materials. The reason is that data-driven models can easily capture the underlying, fine details that represent the visual appearance of materials, which can be difficult or even impossible to model by hand. Measured materials are rapidly becoming a core component in the photo-realistic image synthesis pipeline. ![]()
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