Pan, Y;
Steed, A;
(2019)
Avatar Type Affects Performance of Cognitive Tasks in Virtual Reality.
In:
VRST '19: 25th ACM Symposium on Virtual Reality Software and Technology.
(pp. pp. 1-4).
ACM Press: New York, NY, USA.
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Abstract
Current consumer virtual reality applications typically represent the user by an avatar comprising a simple head/torso and decoupled hands. In the prior work of Steed et al. it was shown that the presence or absence of an avatar could have a significant impact on the cognitive load of the user. We extend that work in two ways. First they only used a full-body avatar with articulated arms, so we add a condition with hands-only representation similar to the majority of current consumer applications. Second we provide a real-world benchmark so as to start to get at the impact of using any immersive system. We validate the prior results: real and full body avatar performance on a memory task is significantly better than no avatar. However the hands only condition is not significantly different than either these two extremes. We discuss why this might be, in particular we discuss the potential for a individual variation in response to the embodiment level.
| Type: | Proceedings paper |
|---|---|
| Title: | Avatar Type Affects Performance of Cognitive Tasks in Virtual Reality |
| Event: | 25th ACM Symposium on Virtual Reality Software and Technology |
| Location: | Parramatta, NSW, Australia |
| Dates: | 12 November 2019 - 15 November 2019 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3359996.3364270 |
| Publisher version: | https://doi.org/10.1145/3359996.3364270 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10085834 |
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