Designing successive target selection in virtual reality via penetrating the intangible interface with handheld controllers. Issue 165 (September 2022)

• Record Type: Journal Article
• Authors: Li, Yang; Sarcar, Sayan; Kim, Kibum; Tu, Huawei; Ren, Xiangshi
• Is Part Of: International journal of human-computer studies. Issue 165(2022)
• Publication Date: 2022-09
• Subjects: Target selection -- Virtual reality -- Text entry; Human-machine systems -- Periodicals; Systems engineering -- Periodicals; Human engineering -- Periodicals; Human engineering; Human-machine systems; Systems engineering; Periodicals; Electronic journals; 004.019
• DOI: 10.1016/j.ijhcs.2022.102835
• Languages: English
• ISSNs: 1071-5819

Abstract

Highlights: We discussed the penetrable feature of intangible displays and found the potential to facilitate target selection coherence among multiple targets. We proposed Sewing, a target selection method in VR for improving the coherence when users successively select multiple targets. With handheld controllers, users can finish selections by penetrating into one target and out directly towards another target. Investigations of Sewing showed that, with the real-life sewing metaphor on the fabric, users can learn and master the Sewing interaction quickly to finish VR target selection tasks. We also implemented SewTyping, a Sewing-based text entry method to facilitate users' VR typing performance. Evaluations revealed that SewTyping achieves promising typing speed (26.57 words per minute) and earned comments from participants as easy and engaging to use. Graphical abstract: Abstract: Empirical research on single target selection in Virtual Reality/Augmented Reality (VR/AR) environments has been studied extensively. However, there is a lack of methods and research on improving the coherence when successively selecting multiple targets. We propose Sewing, a successive target selection method with handheld controllers in VR environments. We leverage real-life sewing as a design metaphor for the selection of multiple targets with one single spatial movement penetrating targets with handheld controllers. We conducted an empirical study to validate the efficiency of selecting multiple targets with Sewing compared with the conventional selection method, which is based on the button pressing metaphor. Results showed that Sewing can provide promising performance and coherence for rapid and accurate target selection. Based on the results, we implemented SewTyping, a Sewing-based VR text entry method to evaluate the applicability of Sewing, and conducted an empirical study to compare the typing performance with two other techniques (Controller Pointing and Drum-like Keyboard). Results showed that 1) SewTyping achieved 26.57 words per minute with a total error rate of 3.68 % and 2) users adapted to the sewing-like movement easily and achieved steady performance with essential practice.