https://orcid.org/0000-0003-1859-8488
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Abstract
Gaze interaction in virtual reality (VR) offers promising advantages in speed and hands-free operation. However, selecting a suitable selection mechanism in VR interfaces with different visual encodings remains a challenge. This research compares two visual input techniques and explores specific visual elements, including field of view (FOV), design style, and number of targets, with the goal of alleviating these problems. The pilot study identifies two search stages, and it also demonstrates a significant effect of FOV on search time. In the formal experiment, a gaze-based trigger experiment is employed to examine the selection performance of fixation and smooth pursuit. The results reveal that optimizing FOV and number of targets improves the triggering efficiency. Furthermore, fixation outperforms pursuit in terms of triggering time and accuracy under the same conditions, while cognitive load during triggering process remains relatively similar. These findings are expected to propose design recommendations to enhance fixation and pursuit within VR interfaces.
Acknowledgments
We would like to appreciate the anonymous reviewers for their constructive comments, and all the participants for actively participating in this experiment.
Disclosure statement
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.
Additional information
Funding
Notes on contributors
Xiaojiao Chen
Xiaojiao Chen is a Professor and Ph.D. mentor at Zhejiang University. She is also a member of the Chinese Ergonomics Society and a member of the Technical Committee on CAD and Graphics. Her research is mainly focused on the human–computer interface, and related cognitive ergonomic evaluation.
Xiaoteng Tang
Xiaoteng Tang is a Ph.D. candidate in design science at the college of computer science and technology, Zhejiang University. His research interests include applying cognitive psychology to human–computer interactions and exploring how to use design methods to improve user experience.
Yonghao Chen
Yonghao Chen is a Ph.D. candidate in design science at the college of computer science and technology, Zhejiang University. His research interests include interaction means such as eye control under VR/AR, and exploring the embeddedness of intelligent interaction methods.
Tengyu Huang
Tengyu Huang is a Master’s degree candidate in the school of art and archeology at Zhejiang University. He majors in ergonomics and psychology and his research interests include applying cognitive psychology to human–computer interactions and providing suggestions to interaction design.
Qinghua Liu
Qinghua Liu is a Ph.D. candidate in design science at the college of computer science and technology, Zhejiang University. His research interests include applying cognitive psychology to human-computer interactions and the application of complex networks.
Jinpeng Yang
Jinpeng Yang is a Master’s degree candidate in the school of art and archaeology at Zhejiang University. He majors in art design and immersive visualization, and his research interests include immersive art and exploration of new interactive methods.
Wenru Qi
Wenru Qi is a Master’s degree candidate for interactive design at Zhejiang University. Her research interests include human–computer interaction. She combines visual perception, cognition, and interaction design to investigating the important factors and mechanisms affecting human–computer interaction.
Xiaosong Wang
Xiaosong Wang is a professor in the School of Arts and Archaeology at Zhejiang University. He obtained Meisterschüler at the Berlin University of the Arts. His current research interests include art and visual experience design.