Impact of Parameter Disentanglement on Collaborative Alignment

Tianyu Song, Alejandro Martin-Gomez, Qiaochu Wang, Arian Mehrfard, Javad Fotouhi, Daniel Roth, Ulrich Eck, Nassir Navab

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

3 Scopus citations

Abstract

The interactive alignment of real and virtual content in AR is often non-trivial. Positional errors along the users view direction frequently lead to the misjudgment of the objects depth. This work takes advantage of alternative users' viewpoints in collaborative settings to mitigate these errors. Furthermore, we systematically restrict the parameters used to control the virtual contents pose and investigate the impact of sharing and disentangling such parameters. Results from this work show that alignment schemes that disentangle the control parameters improve overall alignment accuracy with a similar workload for the users and no significant increase in execution time.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages560-561
Number of pages2
ISBN (Electronic)9781665484022
DOIs
StatePublished - 2022
Event2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022 - Virtual, Online, New Zealand
Duration: 12 Mar 202216 Mar 2022

Publication series

NameProceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022

Conference

Conference2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022
Country/TerritoryNew Zealand
CityVirtual, Online
Period12/03/2216/03/22

Keywords

  • Collaborative interaction
  • Human computer interaction (HCI)
  • Human computer interaction (HCI)
  • Human computer interaction (HCI)
  • Mixed/augmented reality
  • User studies

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