Robust Surface Light Field Modeling

Wei Li, Hui Qiao, Chen Zhao, Zhongqin Wu, Ruigang Yang

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

1 Scopus citations

Abstract

Surface light field advances conventional light field rendering techniques by utilizing geometry information. Using surface light field, real-world objects with complex appearance could be faithfully represented. This capability could play an important role in many VR/AR applications. However, an accurate geometric model is needed for surface light field sampling and processing, which limits its wide usage since many objects of interests are difficult if not impossible to reconstruct with their usually very complex appearances. We propose a novel optimization framework to reduce the dependency of accurate geometry. The key insight is to treat surface light sampling as a multi-view multi-texture optimization problem. Our approach can deal with both model inaccuracy and texture to model misalignment, making it possible to create high-fidelity surface light field models without using high-precision special hardware.

Original languageEnglish
Title of host publicationProceedings - IEEE 1st Conference on Multimedia Information Processing and Retrieval, MIPR 2018
Pages321-327
Number of pages7
ISBN (Electronic)9781538618578
DOIs
StatePublished - Jun 26 2018
Event1st IEEE Conference on Multimedia Information Processing and Retrieval, MIPR 2018 - Miami, United States
Duration: Apr 10 2018Apr 12 2018

Publication series

NameProceedings - IEEE 1st Conference on Multimedia Information Processing and Retrieval, MIPR 2018

Conference

Conference1st IEEE Conference on Multimedia Information Processing and Retrieval, MIPR 2018
Country/TerritoryUnited States
CityMiami
Period4/10/184/12/18

Keywords

  • AR/VR
  • image based rendering
  • light filed
  • surface light filed

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Media Technology

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