Ninja Hands: Using Many Hands to Improve Target Selection in VR

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Standard

Ninja Hands : Using Many Hands to Improve Target Selection in VR. / Schjerlund, Jonas; Hornbæk, Kasper; Bergström, Joanna.

CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2021. 130.

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Harvard

Schjerlund, J, Hornbæk, K & Bergström, J 2021, Ninja Hands: Using Many Hands to Improve Target Selection in VR. in CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems., 130, Association for Computing Machinery, CHI 2021 Virtual Conference on Human Factors in Computing Systems , 08/05/2021. https://doi.org/10.1145/3411764.3445759

APA

Schjerlund, J., Hornbæk, K., & Bergström, J. (2021). Ninja Hands: Using Many Hands to Improve Target Selection in VR. In CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems [130] Association for Computing Machinery. https://doi.org/10.1145/3411764.3445759

Vancouver

Schjerlund J, Hornbæk K, Bergström J. Ninja Hands: Using Many Hands to Improve Target Selection in VR. In CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery. 2021. 130 https://doi.org/10.1145/3411764.3445759

Author

Schjerlund, Jonas ; Hornbæk, Kasper ; Bergström, Joanna. / Ninja Hands : Using Many Hands to Improve Target Selection in VR. CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, 2021.

Bibtex

@inproceedings{c91d146612184778922dd38e41ab2505,
title = "Ninja Hands: Using Many Hands to Improve Target Selection in VR",
abstract = "Selection and manipulation in virtual reality often happen using an avatar{\textquoteright}s hands. However, objects outside the immediate reach require effort to select. We develop a target selection technique called Ninja Hands. It maps the movement of a single real hand to many virtual hands, decreasing the distance to targets. We evaluate Ninja Hands in two studies. The first study shows that compared to a single hand, 4 and 8 hands are significantly faster for selecting targets. The second study complements this finding by using a larger target layout with many distractors. We find no decrease in selection time across 8, 27, and 64 hands, but an increase in the time spent deciding which hand to use. Thereby, net movement time still decreases significantly. In both studies, the physical motion exerted also decreases significantly with more hands. We discuss how these findings can inform future implementations of the Ninja Hands technique.",
author = "Jonas Schjerlund and Kasper Hornb{\ae}k and Joanna Bergstr{\"o}m",
year = "2021",
month = may,
day = "7",
doi = "10.1145/3411764.3445759",
language = "English",
booktitle = "CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems",
publisher = "Association for Computing Machinery",
note = "CHI 2021 Virtual Conference on Human Factors in Computing Systems , CHI'21 ; Conference date: 08-05-2021 Through 13-05-2021",
url = "https://chi2021.acm.org/",

}

RIS

TY - GEN

T1 - Ninja Hands

T2 - CHI 2021 Virtual Conference on Human Factors in Computing Systems

AU - Schjerlund, Jonas

AU - Hornbæk, Kasper

AU - Bergström, Joanna

PY - 2021/5/7

Y1 - 2021/5/7

N2 - Selection and manipulation in virtual reality often happen using an avatar’s hands. However, objects outside the immediate reach require effort to select. We develop a target selection technique called Ninja Hands. It maps the movement of a single real hand to many virtual hands, decreasing the distance to targets. We evaluate Ninja Hands in two studies. The first study shows that compared to a single hand, 4 and 8 hands are significantly faster for selecting targets. The second study complements this finding by using a larger target layout with many distractors. We find no decrease in selection time across 8, 27, and 64 hands, but an increase in the time spent deciding which hand to use. Thereby, net movement time still decreases significantly. In both studies, the physical motion exerted also decreases significantly with more hands. We discuss how these findings can inform future implementations of the Ninja Hands technique.

AB - Selection and manipulation in virtual reality often happen using an avatar’s hands. However, objects outside the immediate reach require effort to select. We develop a target selection technique called Ninja Hands. It maps the movement of a single real hand to many virtual hands, decreasing the distance to targets. We evaluate Ninja Hands in two studies. The first study shows that compared to a single hand, 4 and 8 hands are significantly faster for selecting targets. The second study complements this finding by using a larger target layout with many distractors. We find no decrease in selection time across 8, 27, and 64 hands, but an increase in the time spent deciding which hand to use. Thereby, net movement time still decreases significantly. In both studies, the physical motion exerted also decreases significantly with more hands. We discuss how these findings can inform future implementations of the Ninja Hands technique.

U2 - 10.1145/3411764.3445759

DO - 10.1145/3411764.3445759

M3 - Article in proceedings

BT - CHI '21: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

PB - Association for Computing Machinery

Y2 - 8 May 2021 through 13 May 2021

ER -

ID: 287611757