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Compact and intuitive data-driven BRDF models
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. (VCL)ORCID iD: 0000-0002-3239-8581
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-7765-1747
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-6071-2507
International Computer Institute, Ege University, Izmir, Turkey.
2019 (English)In: The Visual Computer, ISSN 0178-2789, E-ISSN 1432-2315, p. 1-18Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2019. p. 1-18
Keywords [en]
Reflectance modeling, Rendering, Computer graphics
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-162427DOI: 10.1007/s00371-019-01664-zOAI: oai:DiVA.org:liu-162427DiVA, id: diva2:1374654
Available from: 2019-12-02 Created: 2019-12-02 Last updated: 2019-12-03Bibliographically approved

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Tongbuasirilai, TanaboonUnger, JonasKronander, Joel

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