TY - GEN
T1 - PinchLens
T2 - 22nd IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2023
AU - Zhu, Fengyuan
AU - Sidenmark, Ludwig
AU - Sousa, Mauricio
AU - Grossman, Tovi
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - We present PinchLens, a new free-hand target selection technique for acquiring small and dense targets in Virtual Reality. Traditional pinch-based selection does not allow people to precisely manipulate small and dense objects effectively due to tracking and perceptual inaccuracies. Our approach combines spatial magnification, an adaptive control-display gain, and visual feedback to improve selection accuracy. When a user starts the pinching selection process, a magnifying bubble expands the scale of nearby targets, an adaptive control-to-display ratio is applied to the user's hand for precision, and a cursor is displayed at the estimated pinch point for enhanced visual feedback. We performed a user study to compare our technique to traditional pinch selection and several variations to isolate the impact of each of the technique's features. The results showed that PinchLens significantly outperformed traditional pinch selection, reducing error rates from 18.9% to 1.9%. Furthermore, we found that magnification was the dominant feature to produce this improvement, while the adaptive control-display gain and visual cursor of pinch were also helpful in several conditions.
AB - We present PinchLens, a new free-hand target selection technique for acquiring small and dense targets in Virtual Reality. Traditional pinch-based selection does not allow people to precisely manipulate small and dense objects effectively due to tracking and perceptual inaccuracies. Our approach combines spatial magnification, an adaptive control-display gain, and visual feedback to improve selection accuracy. When a user starts the pinching selection process, a magnifying bubble expands the scale of nearby targets, an adaptive control-to-display ratio is applied to the user's hand for precision, and a cursor is displayed at the estimated pinch point for enhanced visual feedback. We performed a user study to compare our technique to traditional pinch selection and several variations to isolate the impact of each of the technique's features. The results showed that PinchLens significantly outperformed traditional pinch selection, reducing error rates from 18.9% to 1.9%. Furthermore, we found that magnification was the dominant feature to produce this improvement, while the adaptive control-display gain and visual cursor of pinch were also helpful in several conditions.
KW - Human computer interaction (HCI)
KW - Human-centered computing
KW - Interaction techniques
UR - https://www.scopus.com/pages/publications/85180375773
UR - https://www.scopus.com/pages/publications/85180375773#tab=citedBy
U2 - 10.1109/ISMAR59233.2023.00139
DO - 10.1109/ISMAR59233.2023.00139
M3 - Conference contribution
AN - SCOPUS:85180375773
T3 - Proceedings - 2023 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2023
SP - 1221
EP - 1230
BT - Proceedings - 2023 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2023
A2 - Bruder, Gerd
A2 - Olivier, Anne-Helene
A2 - Cunningham, Andrew
A2 - Peng, Evan Yifan
A2 - Grubert, Jens
A2 - Williams, Ian
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 16 October 2023 through 20 October 2023
ER -