TY - GEN
T1 - Layerable Apps
T2 - 21st IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2022
AU - Huynh, Brandon
AU - Wysopal, Abby
AU - Ross, Vivian
AU - Orlosky, Jason
AU - Hollerer, Tobias
N1 - Funding Information:
This work was supported in part by the Office of Naval Research, under grants #N00014-19-1-2553, #N00174-19-1-0024, and #N62909-18-1-2036, and by grant #21H03482 from the Japan Society for the Promotion of Science. Additional funding came from NSF award IIS-1911230.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Current augmented reality (AR) interfaces are often designed for interacting with one application at a time, significantly limiting a user's ability to concurrently interact with and switch between multiple applications or modalities that could run in parallel. In this work, we introduce an application model called Layerable Apps, which supports a variety of AR application types while enabling multitasking through concurrent execution, fast application switching, and the ability to layer application views to adjust the degree of augmentation to the user's preference. We evaluated Layerable Apps through a within-subjects user study (n=44), compared against a traditional single-focus application model on a split-information task involving the simultaneous use of multiple applications. We report the results of our study, where we found differences in quantitative task performance, favoring Layerable mode. We also analyzed app usage patterns, spatial awareness, and overall preferences between both modes as well as between experienced and novice AR users.
AB - Current augmented reality (AR) interfaces are often designed for interacting with one application at a time, significantly limiting a user's ability to concurrently interact with and switch between multiple applications or modalities that could run in parallel. In this work, we introduce an application model called Layerable Apps, which supports a variety of AR application types while enabling multitasking through concurrent execution, fast application switching, and the ability to layer application views to adjust the degree of augmentation to the user's preference. We evaluated Layerable Apps through a within-subjects user study (n=44), compared against a traditional single-focus application model on a split-information task involving the simultaneous use of multiple applications. We report the results of our study, where we found differences in quantitative task performance, favoring Layerable mode. We also analyzed app usage patterns, spatial awareness, and overall preferences between both modes as well as between experienced and novice AR users.
KW - Human computer interaction (HCI)
KW - Human-centered computing
KW - Interaction design
KW - Interaction design process and methods
KW - Interaction paradigms
KW - Mixed/augmented reality
KW - User interface design
UR - http://www.scopus.com/inward/record.url?scp=85146424135&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146424135&partnerID=8YFLogxK
U2 - 10.1109/ISMAR55827.2022.00104
DO - 10.1109/ISMAR55827.2022.00104
M3 - Conference contribution
AN - SCOPUS:85146424135
T3 - Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2022
SP - 857
EP - 863
BT - Proceedings - 2022 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2022
A2 - Duh, Henry
A2 - Williams, Ian
A2 - Grubert, Jens
A2 - Jones, J. Adam
A2 - Zheng, Jianmin
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 October 2022 through 21 October 2022
ER -