How Foot Tracking Matters: The Impact of an Animated Self-Avatar on Interaction, Embodiment and Presence in Shared Virtual Environments.

SVE foot tracking interaction self-avatar virtual reality

Journal

Frontiers in robotics and AI
ISSN: 2296-9144
Titre abrégé: Front Robot AI
Pays: Switzerland
ID NLM: 101749350

Informations de publication

Date de publication:
2019
Historique:
received: 30 09 2018
accepted: 09 10 2019
entrez: 27 1 2021
pubmed: 30 10 2019
medline: 30 10 2019
Statut: epublish

Résumé

The use of a self-avatar representation in head-mounted displays has been shown to have important effects on user behavior. However, relatively few studies focus on feet and legs. We implemented a shared virtual reality for consumer virtual reality systems where each user could be represented by a gender-matched self-avatar controlled by multiple trackers. The self-avatar allowed users to see their feet, legs and part of their torso when they looked down. We implemented an experiment where participants worked together to solve jigsaw puzzles. Participants experienced either no-avatar, a self-avatar with floating feet, or a self-avatar with tracked feet, in a between-subjects manipulation. First, we found that participants could solve the puzzle more quickly with self-avatars than without self-avatars; but there was no significant difference between the latter two conditions, solely on task completion time. Second, we found participants with tracked feet placed their feet statistically significantly closer to obstacles than participants with floating feet, whereas participants who did not have a self-avatar usually ignored obstacles. Our post-experience questionnaire results confirmed that the use of a self-avatar has important effects on presence and interaction. Together the results show that although the impact of animated legs might be subtle, it does change how users behave around obstacles. This could have important implications for the design of virtual spaces for applications such as training or behavioral analysis.

Identifiants

pubmed: 33501119
doi: 10.3389/frobt.2019.00104
pmc: PMC7805935
doi:

Types de publication

Journal Article

Langues

eng

Pagination

104

Informations de copyright

Copyright © 2019 Pan and Steed.

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Auteurs

Ye Pan (Y)

Virtual Environments and Computer Graphics Group, Department of Computer Science, University College London, London, United Kingdom.

Anthony Steed (A)

Virtual Environments and Computer Graphics Group, Department of Computer Science, University College London, London, United Kingdom.

Classifications MeSH