Compact and intuitive data-driven BRDF models

Küçük Resim Yok

Tarih

2020

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Springer

Erişim Hakkı

info:eu-repo/semantics/openAccess

Özet

Measured materials are rapidly becoming a core component in the photo-realistic image synthesis pipeline. 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. 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. This paper presents two new data-driven BRDF models specifically designed for 1D separability. 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. 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. 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. © 2019, The Author(s).

Açıklama

Anahtar Kelimeler

Computer graphics, Reflectance modeling, Rendering, Computer graphics, Importance sampling, Approximation errors, Data-driven model, Factored models, Numerical errors, Photo realistic image synthesis, Reflectance model, Rendering, Visual appearance, Rendering (computer graphics)

Kaynak

Visual Computer

WoS Q Değeri

Scopus Q Değeri

Q2

Cilt

36

Sayı

4

Künye