TY - GEN
T1 - Exploring Text Selection in Augmented Reality Systems
AU - Liu, Xinyi
AU - Meng, Xuanru
AU - Spittle, Becky
AU - Xu, Wenge
AU - Gao, Bo Yu
AU - Liang, Hai Ning
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/12/27
Y1 - 2022/12/27
N2 - Text selection is a common and essential activity during text interaction in all interactive systems. As Augmented Reality (AR) head-mounted displays (HMDs) become more widespread, they will need to provide effective interaction techniques for text selection that ensure users can complete a range of text manipulation tasks (e.g., to highlight, copy, and paste text, send instant messages, and browse the web). As a relatively new platform, text selection in AR is largely unexplored and the suitability of interaction techniques supported by current AR HMDs for text selection tasks is unclear. This research aims to fill this gap and reports on an experiment with 12 participants, which compares the performance and usability (user experience and workload) of four possible techniques (Hand+Pinch, Hand+Dwell, Head+Pinch, and Head+Dwell). Our results suggest that Head+Dwell should be the default selection technique, as it is relatively fast, has the lowest error rate and workload, and has the highest-rated user experience and social acceptance.
AB - Text selection is a common and essential activity during text interaction in all interactive systems. As Augmented Reality (AR) head-mounted displays (HMDs) become more widespread, they will need to provide effective interaction techniques for text selection that ensure users can complete a range of text manipulation tasks (e.g., to highlight, copy, and paste text, send instant messages, and browse the web). As a relatively new platform, text selection in AR is largely unexplored and the suitability of interaction techniques supported by current AR HMDs for text selection tasks is unclear. This research aims to fill this gap and reports on an experiment with 12 participants, which compares the performance and usability (user experience and workload) of four possible techniques (Hand+Pinch, Hand+Dwell, Head+Pinch, and Head+Dwell). Our results suggest that Head+Dwell should be the default selection technique, as it is relatively fast, has the lowest error rate and workload, and has the highest-rated user experience and social acceptance.
KW - Augmented Reality
KW - Pointing Methods
KW - Selection Mechanisms
KW - Text Selection
KW - User Study
UR - https://www.scopus.com/pages/publications/85147246189
U2 - 10.1145/3574131.3574459
DO - 10.1145/3574131.3574459
M3 - Conference Proceeding
AN - SCOPUS:85147246189
T3 - Proceedings - VRCAI 2022: 18th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry
BT - Proceedings - VRCAI 2022
A2 - Spencer, Stephen N.
PB - Association for Computing Machinery, Inc
T2 - 18th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry, VRCAI 2022
Y2 - 27 December 2022 through 29 December 2022
ER -