liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Learning Based Compression of Surface Light Fields for Real-time Rendering of Global Illumination Scenes
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology. (Computer Graphics and Image Processing)
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology. (Computer Graphics and Image Processing)
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology. (Computer Graphics and Image Processing)ORCID iD: 0000-0002-7765-1747
2013 (English)In: Proceedings of ACM SIGGRAPH ASIA 2013, ACM Press, 2013Conference paper, Published paper (Refereed)
Abstract [en]

We present an algorithm for compression and real-time rendering of surface light fields (SLF) encoding the visual appearance of objects in static scenes with high frequency variations. We apply a non-local clustering in order to exploit spatial coherence in the SLFdata. To efficiently encode the data in each cluster, we introducea learning based approach, Clustered Exemplar Orthogonal Bases(CEOB), which trains a compact dictionary of orthogonal basispairs, enabling efficient sparse projection of the SLF data. In ad-dition, we discuss the application of the traditional Clustered Principal Component Analysis (CPCA) on SLF data, and show that inmost cases, CEOB outperforms CPCA, K-SVD and spherical harmonics in terms of memory footprint, rendering performance andreconstruction quality. Our method enables efficient reconstructionand real-time rendering of scenes with complex materials and lightsources, not possible to render in real-time using previous methods.

Place, publisher, year, edition, pages
ACM Press, 2013.
Keyword [en]
computer graphics, global illumination, real-time, machine learning
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-99433DOI: 10.1145/2542355.2542385ISBN: 978-1-4503-2629-2 (print)OAI: oai:DiVA.org:liu-99433DiVA: diva2:657087
Conference
SIGGRAPH Asia, 19-22 November 2013, Hong Kong
Projects
VPS
Funder
Swedish Foundation for Strategic Research , IIS11-0081Swedish Research Council
Available from: 2013-10-17 Created: 2013-10-17 Last updated: 2015-09-22Bibliographically approved

Open Access in DiVA

Paper preprint(11366 kB)326 downloads
File information
File name FULLTEXT01.pdfFile size 11366 kBChecksum SHA-512
2d00733ef73f837914da20ef748347b6a34657330d5a9dffdc1177ab5e9ae3ce035597fb7b973f7ecb8426f897ab7d7199c104a9131c061e69e2f8868e5d97a2
Type fulltextMimetype application/pdf

Other links

Publisher's full text

Authority records BETA

Miandji, EhsanKronander, JoelUnger, Jonas

Search in DiVA

By author/editor
Miandji, EhsanKronander, JoelUnger, Jonas
By organisation
Media and Information TechnologyThe Institute of Technology
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
Total: 326 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 281 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf