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Robust Surface Light Field Modeling

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

Producción científica: Conference contributionrevisión exhaustiva

2 Citas (Scopus)

Resumen

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.

Idioma originalEnglish
Título de la publicación alojadaProceedings - IEEE 1st Conference on Multimedia Information Processing and Retrieval, MIPR 2018
Páginas321-327
Número de páginas7
ISBN (versión digital)9781538618578
DOI
EstadoPublished - jun 26 2018
Evento1st IEEE Conference on Multimedia Information Processing and Retrieval, MIPR 2018 - Miami, United States
Duración: abr 10 2018abr 12 2018

Serie de la publicación

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

Conference

Conference1st IEEE Conference on Multimedia Information Processing and Retrieval, MIPR 2018
País/TerritorioUnited States
CiudadMiami
Período4/10/184/12/18

Nota bibliográfica

Publisher Copyright:
© 2018 IEEE.

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Media Technology

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