PizzaText : Text Entry for Virtual Reality Systems Using Dual Thumbsticks

We present PizzaText, a circular keyboard layout technique for text entry in virtual reality (VR) environments that uses the dual thumbsticks of a hand-held game controller. Text entry is a common activity in VR environments but remains challenging with existing techniques and keyboard layouts that...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics. - 1996. - 24(2018), 11 vom: 05. Nov., Seite 2927-2935
1. Verfasser: Yu, Difeng (VerfasserIn)
Weitere Verfasser: Fan, Kaixuan, Zhang, Heng, Monteiro, Diego, Xu, Wenge, Liang, Hai-Ning
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2018
Zugriff auf das übergeordnete Werk:IEEE transactions on visualization and computer graphics
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
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520 |a We present PizzaText, a circular keyboard layout technique for text entry in virtual reality (VR) environments that uses the dual thumbsticks of a hand-held game controller. Text entry is a common activity in VR environments but remains challenging with existing techniques and keyboard layouts that is largely based on QWERTY. Our technique makes text entry simple, easy, and efficient, even for novice users. The technique uses a hand-held controller because it is still an important input device for users to interact with VR environments. To allow rapid search of characters, PizzaText divides a circle into slices and each slice contains 4 characters. To enable fast selection, the user uses the right thumbstick for traversing the slices, and the left thumbstick for choosing the letters. The design of PizzaText is based on three criteria: efficiency, learnability, and ease-of-use. In our first study, six potential layouts are considered and evaluated. The results lead to a design with 7 slices and 4 letters per slice. The final design is evaluated in a five-day study with 10 participants. The results show that novice users can achieve an average of 8.59 Words per Minute (WPM), while expert users are able to reach 15.85 WPM, with just two hours of training 
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700 1 |a Fan, Kaixuan  |e verfasserin  |4 aut 
700 1 |a Zhang, Heng  |e verfasserin  |4 aut 
700 1 |a Monteiro, Diego  |e verfasserin  |4 aut 
700 1 |a Xu, Wenge  |e verfasserin  |4 aut 
700 1 |a Liang, Hai-Ning  |e verfasserin  |4 aut 
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