2023
DOI: 10.1109/tvcg.2023.3247098
|View full text |Cite
|
Sign up to set email alerts
|

Text Input for Non-Stationary XR Workspaces: Investigating Tap and Word-Gesture Keyboards in Virtual and Augmented Reality

Abstract: Fig. 1: The virtual keyboard layout is based on the traditional layout of physical keyboards. (A) Shows the tap keyboard in video see-through augmented reality (VST AR) and (B) the swipe keyboard in virtual reality (VR) with a black tail following the user's controller. For the VR condition, we created an accurate digital twin of the real physical room. In the VST AR condition, the real world was captured by the video see-through capabilities of the XR device. To enable precise interaction, the user holds the … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
19
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
6
2

Relationship

1
7

Authors

Journals

citations
Cited by 24 publications
(20 citation statements)
references
References 98 publications
1
19
0
Order By: Relevance
“…This work focuses on analyzing the relationship between stress and head movements while using an AR application. Due to the foreseen spreading of AR solutions for working [52] and learning activities [53], we considered a static task (e.g., reading, informative training, tutorial watching, data analysis [54]) and analyzed several head movement features to determine whether they show a significant difference during a stress situation. The most significant features have been used to define a Machine Learning (ML) classifier able to detect the presence of stress.…”
Section: Proposed Methodsmentioning
confidence: 99%
“…This work focuses on analyzing the relationship between stress and head movements while using an AR application. Due to the foreseen spreading of AR solutions for working [52] and learning activities [53], we considered a static task (e.g., reading, informative training, tutorial watching, data analysis [54]) and analyzed several head movement features to determine whether they show a significant difference during a stress situation. The most significant features have been used to define a Machine Learning (ML) classifier able to detect the presence of stress.…”
Section: Proposed Methodsmentioning
confidence: 99%
“…Furthermore, they measured more head movement in the AR condition, which could be an indicator of absent or conflicting depth cues that participants then counteracted with motion parallaxes. Kern et al [23] investigated different keyboard input modalities in VR and VST AR. Contrary to Krichenbauer et al's findings [26], Kern et al found a significantly higher completion time in VST AR than in VR, i.e., participants typed faster in VR.…”
Section: Related Workmentioning
confidence: 99%
“…Text input might require more cognitive resources. Kern et al [23] explain their results with the Congruence and Plausibility (CaP) model by Latoschik and Wienrich [28] which defines a manipulation space with three layers: the sensation, the perception, and the cognition layer (i.e., bottom-up to top-down). On each layer, (in)congruence can be manipulated, resulting in a condition of plausibility.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…The input speed of physical keyboards could reach 30 words per minute (WPM), with an accuracy rate of around 80% [ 11 ]. Touch screens and controllers offer better portability and typing speeds exceeding 8 WPM, but they are heavy and can detract from the user’s sense of immersion in the VR environment [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. Additionally, some text input methods based on controllers involve a substantial learning cost.…”
Section: Introductionmentioning
confidence: 99%