Literature DB >> 30762551

RingText: Dwell-free and hands-free Text Entry for Mobile Head-Mounted Displays using Head Motions.

Wenge Xu, Hai-Ning Liang, Yuxuan Zhao, Tianyu Zhang, Difeng Yu, Diego Monteiro, Yong Yue.   

Abstract

In this paper, we present a case for text entry using a circular keyboard layout for mobile head-mounted displays (HMDs) that is dwell-free and does not require users to hold a dedicated input device for letter selection. To support the case, we have implemented RingText whose design is based on a circular layout with two concentric circles. The outer circle is subdivided into regions containing letters. Selection is made by using a virtual cursor controlled by the user's head movements-entering a letter region triggers a selection and moving back into the inner circle resets the selection. The design of RingText follows an iterative process, where we initially conduct one first study to investigate the optimal number of letters per region, inner circle size, and alphabet starting location. We then optimize its design by selecting the most suitable features from the first study: one letter per region, narrowing the trigger area to lower error rates, and creating candidate regions that incorporate two suggested words to appear next to the current letter region (close to the cursor) using a dynamic (rather than fixed) approach. Our second study compares text entry performance of RingText with four other hands-free techniques and the results show that RingText outperforms them. Finally, we run a third study lasting four consecutive days with 10 participants (5 novice users and 5 expert users) doing two daily sessions and the results show that RingText is quite efficient and yields a low error rate. At the end of the eighth session, the novice users can achieve a text entry speed of 11.30 WPM after 60 minutes of training while the expert (more experienced) users can reach an average text entry speed of 13.24 WPM after 90 minutes of training.

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Year:  2019        PMID: 30762551     DOI: 10.1109/TVCG.2019.2898736

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  2 in total

1.  BioMove: Biometric User Identification from Human Kinesiological Movements for Virtual Reality Systems.

Authors:  Ilesanmi Olade; Charles Fleming; Hai-Ning Liang
Journal:  Sensors (Basel)       Date:  2020-05-22       Impact factor: 3.576

2.  Results and Guidelines From a Repeated-Measures Design Experiment Comparing Standing and Seated Full-Body Gesture-Based Immersive Virtual Reality Exergames: Within-Subjects Evaluation.

Authors:  Wenge Xu; Hai-Ning Liang; Qiuyu He; Xiang Li; Kangyou Yu; Yuzheng Chen
Journal:  JMIR Serious Games       Date:  2020-07-27       Impact factor: 4.143

  2 in total

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