Skip to main navigation Skip to search Skip to main content

A data-driven BSDF framework

  • Ege University
  • Ernest Orlando Lawrence Berkeley National Laboratory

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present a data-driven Bidirectional Scattering Distribution Function (BSDF) representation and a model-free technique that preserves the integrity of the original data and interpolates reflection as well as transmission functions for arbitrary materials. Our interpolation technique employs Radial Basis Functions (RBFs), Radial Basis Systems (RBSs) and displacement techniques to track peaks in the distribution. The proposed data-driven BSDF representation can be used to render arbitrary BSDFs and includes an efficient Monte Carlo importance sampling scheme. We show that our data-driven BSDF framework can be used to represent measured BSDFs that are visually plausible and demonstrably accurate.

Original languageEnglish
Title of host publicationSIGGRAPH 2016 - ACM SIGGRAPH 2016 Posters
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450343718
DOIs
Publication statusPublished - 24 Jul 2016
EventACM International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2016 - Anaheim, United States
Duration: 24 Jul 201628 Jul 2016

Publication series

NameSIGGRAPH 2016 - ACM SIGGRAPH 2016 Posters

Conference

ConferenceACM International Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 2016
Country/TerritoryUnited States
CityAnaheim
Period24/07/1628/07/16

Keywords

  • Appearance modeling
  • BSDF
  • Data interpolation
  • Global illumination
  • Rendering

Fingerprint

Dive into the research topics of 'A data-driven BSDF framework'. Together they form a unique fingerprint.

Cite this