Iteratively Adapting Avatars using Task-Integrated Optimisation
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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Iteratively Adapting Avatars using Task-Integrated Optimisation. / McIntosh, Jess; Zajac, Hubert Dariusz; Stefan, Andreea; Bergström, Joanna; Hornbæk, Kasper.
Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology. 1. udg. https://dl.acm.org/doi/abs/10.1145/3379337.3415832 : Association for Computing Machinery, 2020. s. 709–721.Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - Iteratively Adapting Avatars using Task-Integrated Optimisation
AU - McIntosh, Jess
AU - Zajac, Hubert Dariusz
AU - Stefan, Andreea
AU - Bergström, Joanna
AU - Hornbæk, Kasper
PY - 2020/10/1
Y1 - 2020/10/1
N2 - Virtual Reality allows users to embody avatars that do not match their real bodies. Earlier work has selected changes to the avatar arbitrarily and it therefore remains unclear how to change avatars to improve users' performance. We propose a systematic approach for iteratively adapting the avatar to perform better for a given task based on users' performance. The approach is evaluated in a target selection task, where the forearms of the avatar are scaled to improve performance. A comparison between the optimised and real arm lengths shows a significant reduction in average tapping time by 18.7%, for forearms multiplied in length by 5.6. Additionally, with the adapted avatar, participants moved their real body and arms significantly less, and subjective measures show reduced physical demand and frustration. In a second study, we modify finger lengths for a linear tapping task to achieve a better performing avatar, which demonstrates the generalisability of the approach.
AB - Virtual Reality allows users to embody avatars that do not match their real bodies. Earlier work has selected changes to the avatar arbitrarily and it therefore remains unclear how to change avatars to improve users' performance. We propose a systematic approach for iteratively adapting the avatar to perform better for a given task based on users' performance. The approach is evaluated in a target selection task, where the forearms of the avatar are scaled to improve performance. A comparison between the optimised and real arm lengths shows a significant reduction in average tapping time by 18.7%, for forearms multiplied in length by 5.6. Additionally, with the adapted avatar, participants moved their real body and arms significantly less, and subjective measures show reduced physical demand and frustration. In a second study, we modify finger lengths for a linear tapping task to achieve a better performing avatar, which demonstrates the generalisability of the approach.
U2 - 10.1145/3379337.3415832
DO - 10.1145/3379337.3415832
M3 - Article in proceedings
SN - 978-1-4503-7514-6
SP - 709
EP - 721
BT - Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology
PB - Association for Computing Machinery
CY - https://dl.acm.org/doi/abs/10.1145/3379337.3415832
T2 - 3rd Annual ACM Symposium on User Interface Software and Technology - UIST' 20
Y2 - 20 October 2020 through 23 October 2020
ER -
ID: 253030789