Hierarchical Rendering System Based on Viewpoint Prediction in Virtual Reality

Ping Lu, Fang Zhu, Ping Li, Jinman Kim, Bin Sheng, Lijuan Mao

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Virtual reality (VR) systems use multi-modal interfaces to explore three-dimensional virtual worlds. During exploration, the user may look at different objects of interest or in different directions. The field of view of human vision is 135× 160, but the one requiring the highest resolution is only in 1.5× 2. It is estimated that in modern VR, only 4% of the pixel resources of the head-mounted display are mapped to the visual center. Therefore, allocating more computing resources to the visual center and allocating fewer viewpoint prediction rendering techniques elsewhere can greatly speed up the rendering of the scene, especially for VR devices equipped with eye trackers. However, eye trackers as additional equipment may be relatively expensive and be harder to use, at the same time, there is considerable work to be done in the development of eye trackers and their integration with commercial head-mounted equipment. Therefore, this article uses an eye-head coordination model combined with the saliencey of the scene to predict the gaze position, and then uses a hybrid method of Level of Detail (LOD) and grid degeneration to reduce rendering time as much as possible without losing the perceived details and required calculations.

Original languageEnglish
Title of host publicationAdvances in Computer Graphics - 37th Computer Graphics International Conference, CGI 2020, Proceedings
EditorsNadia Magnenat-Thalmann, Constantine Stephanidis, George Papagiannakis, Enhua Wu, Daniel Thalmann, Bin Sheng, Jinman Kim, Marina Gavrilova
PublisherSpringer Science and Business Media Deutschland GmbH
Pages24-32
Number of pages9
ISBN (Print)9783030618636
DOIs
Publication statusPublished - 2020
Event37th Computer Graphics International Conference, CGI 2020 - Geneva, Switzerland
Duration: 20 Oct 202023 Oct 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12221 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference37th Computer Graphics International Conference, CGI 2020
Country/TerritorySwitzerland
CityGeneva
Period20/10/2023/10/20

Keywords

  • Eye-head coordination
  • Hand track
  • Hierarchical rendering
  • LOD
  • VR

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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