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Quantifiable Fine-Grain Occlusion Removal Assistance for Efficient VR Exploration

  • Jian Wu
  • , Lili Wang*
  • , Hui Zhang
  • , Voicu Popescu
  • *Corresponding author for this work
  • Beihang University
  • Peng Cheng Laboratory
  • Purdue University

Research output: Contribution to journalArticlepeer-review

Abstract

This article presents an occlusion management approach that handles fine-grain occlusions, and that quantifies and localizes occlusions as a user explores a virtual environment (VE). Fine-grain occlusions are handled by finding the VE region where they occur, and by constructing a multiperspective visualization that lets the user explore the region from the current location, with intuitive head motions, without first having to walk to the region. VE geometry close to the user is rendered conventionally, from the user's viewpoint, to anchor the user, avoiding disorientation and simulator sickness. Given a viewpoint, residual occlusions are quantified and localized as VE voxels that cannot be seen from the given viewpoint but that can be seen from nearby viewpoints. This residual occlusion quantification and localization helps the user ascertain that a VE region has been explored exhaustively. The occlusion management approach was tested in three controlled studies, which confirmed the exploration efficiency benefit of the approach, and in perceptual experiments, which confirmed that exploration efficiency does not come at the cost of reducing spatial awareness and sense of presence, or of increasing simulator sickness.

Original languageEnglish
Pages (from-to)3154-3167
Number of pages14
JournalIEEE Transactions on Visualization and Computer Graphics
Volume28
Issue number9
DOIs
StatePublished - 1 Sep 2022

Keywords

  • VR exploration
  • fine grain disocclusion
  • graph camera
  • multiperspective visualization
  • occlusion quantification

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