An intuitive control space for material appearance

Serrano, Ana (Universidad de Zaragoza) ; Gutierrez, Diego (Universidad de Zaragoza) ; Myszkowski, Karol ; Seidel, Hans-Peter ; Masia, Belen (Universidad de Zaragoza)
An intuitive control space for material appearance
Financiación H2020 / H2020 Funds
Resumen: Many different techniques for measuring material appearance have been proposed in the last few years. These have produced large public datasets, which have been used for accurate, data-driven appearance modeling. However, although these datasets have allowed us to reach an unprecedented level of realism in visual appearance, editing the captured data remains a challenge. In this paper, we present an intuitive control space for predictable editing of captured BRDF data, which allows for artistic creation of plausible novel material appearances, bypassing the difficulty of acquiring novel samples. We first synthesize novel materials, extending the existing MERL dataset up to 400 mathematically valid BRDFs. We then design a large-scale experiment, gathering 56,000 subjective ratings on the high-level perceptual attributes that best describe our extended dataset of materials. Using these ratings, we build and train networks of radial basis functions to act as functionals mapping the perceptual attributes to an underlying PCA-based representation of BRDFs. We show that our functionals are excellent predictors of the perceived attributes of appearance. Our control space enables many applications, including intuitive material editing of a wide range of visual properties, guidance for gamut mapping, analysis of the correlation between perceptual attributes, or novel appearance similarity metrics. Moreover, our methodology can be used to derive functionals applicable to classic analytic BRDF representations. We release our code and dataset publicly, in order to support and encourage further research in this direction.
Idioma: Inglés
DOI: 10.1145/2980179.2980242
Año: 2016
Publicado en: ACM TRANSACTIONS ON GRAPHICS 35, 6 (2016), 186 [12 pp]
ISSN: 0730-0301

Factor impacto JCR: 4.088 (2016)
Categ. JCR: COMPUTER SCIENCE, SOFTWARE ENGINEERING rank: 1 / 106 = 0.009 (2016) - Q1 - T1
Factor impacto SCIMAGO: 1.946 - Computer Graphics and Computer-Aided Design (Q1)

Financiación: info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON
Financiación: info:eu-repo/grantAgreement/ES/MINECO/TIN2013-41857-P
Tipo y forma: Artículo (PostPrint)
Área (Departamento): Área Lenguajes y Sistemas Inf. (Dpto. Informát.Ingenie.Sistms.)

Derechos Reservados Derechos reservados por el editor de la revista


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