Climbing Keyboard: A Tilt-Based Selection Keyboard Entry for Virtual Reality

Abstract

Text input is one of the common interaction tasks in virtual environments. However, current inputting methods (e.g., laser-input: aim-and-shoot technique) have many limitations, such as inefficiency, lack of precision, and fatigue of long-text inputting. We propose a Climbing Keyboard method to allow easier, faster, and more accurate text input, and use tilt instead of precise aiming. The selected target changes from a specific letter to a group of letters with such a tilt-based interaction based on the QWERTY layout, which aims to reduce the learning cost, especially for novice users. Meanwhile, expert users can focus on the screen without looking at the keyboard. We designed three user studies to evaluate the performance of proposed method, including the verification of the usability of the tilt interaction method in the first study, optimization of the tilt angle range in the second study, and evaluation of the learning curve of Climbing keyboard in the last study. Our results showed that participants can reach 16.48 words per minute after an hours of training.

Acknowledgements

We thank the participants in the user study for their availability and significant comments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study has been partially supported by National Natural Science Foundation of China [61872164] and Program of Science and Technology Development Plan of Jilin Province of China [20220201147GX].

Notes on contributors

Junfeng Huang

Junfeng Huang is a postgraduate student of the Jilin University on his topic of target selection techniques in Virtual Reality. He has a background in computer science and technique. He wanted to gain expertise in Human Computer Interaction and VR.

Minghui Sun

Minghui Sun is currently an Associate Professor with the College of Computer Science and Technology, Jilin University, China. He is interested in using HCI methods to solve challenging real-world computing problems in many areas, including tactile interface, pen-based interface, and tangible interface.

Jun Qin

Jun Qin is currently a Lecturer of Changchun University of Science and Technology. His main researches focus on image processing and tracking with both deep learning methods and traditional methods, especially in the field of image segmentation and image fusion.

BoYu Gao

Boyu Gao is currently an Associate Professor of Jinan University. His researches mainly lie on the intersection of Virtual Reality (VR), Human-Computer Interaction (HCI), and Artificial Intelligence (AI), specifically, focusing on designing multimodal feedback, evoking believable experiences in virtual environments and perceptual-based user interfaces.

Guihe Qin

Guihe Qin is currently a Professor with the College of Computer Science and Technology, Jilin University, China. His research interests include intelligent control and embedded systems, computer vision, and intelligent connected vehicle.