Text Entry in Virtual Reality: A Comparison of 2D and 3D Keyboard Layouts

2020 ◽  
pp. 450-460
Author(s):  
Caglar Yildirim ◽  
Ethan Osborne
Keyword(s):  
Virtual Reality ◽  
Text Entry ◽  
2D And 3D

scholarly journals Text Input in Virtual Reality: A Preliminary Evaluation of the Drum-Like VR Keyboard

Technologies ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 31 ◽  
Author(s):  
Costas Boletsis ◽  
Stian Kongsvik
Keyword(s):  
Virtual Reality ◽  
User Experience ◽  
Total Error ◽  
Preliminary Evaluation ◽  
Text Entry ◽  
Entry Rate ◽  
Drum Set ◽  
Text Input ◽  
Total Error Rate ◽  
Experience Questionnaire

The drum-like virtual reality (VR) keyboard is a contemporary, controller-based interface for text input in VR that uses a drum set metaphor. The controllers are used as sticks which, through downward movements, “press” the keys of the virtual keyboard. In this work, a preliminary feasibility study of the drum-like VR keyboard is described, focusing on the text entry rate and accuracy as well as its usability and the user experience it offers. Seventeen participants evaluated the drum-like VR keyboard by having a typing session and completing a usability and a user experience questionnaire. The interface achieved a good usability score, positive experiential feedback around its entertaining and immersive qualities, a satisfying text entry rate (24.61 words-per-minute), as well as moderate-to-high total error rate (7.2%) that can probably be further improved in future studies. The work provides strong indications that the drum-like VR keyboard can be an effective and entertaining way to type in VR.

LEA: Software System for Multimedia and Virtual-Reality Web-Based Education and Training

2006 ◽  
Author(s):  
Tamer M. Wasfy
Keyword(s):  
Virtual Reality ◽  
Knowledge Base ◽  
Education And Training ◽  
Software System ◽  
Web Based ◽  
Fully Integrated ◽  
Step Process ◽  
Base Engine ◽  
2D And 3D ◽  
And Training

LEA (Learning Environments Agent) is a web-based software system for advanced multimedia and virtual-reality education and training. LEA consists of three fully integrated components: (1) unstructured knowledge-base engine for lecture delivery; (2) structured hierarchical process knowledge-base engine for step-by-step process training; and (3) hierarchical rule-based expert system for natural-language understanding. In addition, LEA interfaces with components which provide the following capabilities: 3D near photo-realistic interactive virtual environments; 2D animated multimedia; near-natural synthesized text-to-speech, speech recognition, near-photorealistic animated virtual humans to act as instructors and assistants; and socket-based network communication. LEA provides the following education and training functions: multimedia lecture delivery; virtual-reality based step-by-step process training; and testing capability. LEA can deliver compelling multimedia lectures and content in science fields (such as engineering, physics, math, and chemistry) that include synchronized: animated 2D and 3D graphics, speech, and written/highlighted text. In addition, it can be used to deliver step-by-step process training in a compelling near-photorealistic 3D virtual environment. In this paper the LEA system is presented along with typical educational and training applications.

Multimodal interaction for 2D and 3D environments [virtual reality]

1999 ◽  
Vol 19 (4) ◽  
pp. 10-13 ◽  
Author(s):  
P. Cohen ◽  
D. McGee ◽  
S. Oviatt ◽  
L. Wu ◽  
J. Clow ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Multimodal Interaction ◽  
3D Environments ◽  
2D And 3D

scholarly journals INFORMATION AND MEMORY-BASED ANALYSIS FOR DECODING OF THE HUMAN LEARNING BETWEEN NORMAL AND VIRTUAL REALITY (VR) CONDITIONS

Fractals ◽  
2021 ◽  
Vol 29 (03) ◽  
pp. 2150163
Author(s):  
HAMIDREZA NAMAZI ◽  
MOHAMMAD HOSSEIN BABINI ◽  
KAMIL KUCA ◽  
ONDREJ KREJCAR
Keyword(s):  
Virtual Reality ◽  
Shannon Entropy ◽  
Mathematical Analysis ◽  
Strong Correlation ◽  
Hurst Exponent ◽  
Human Learning ◽  
Learning Ability ◽  
Eeg Signals ◽  
2D And 3D ◽  
Electroencephalogram Eeg

In this paper, we investigated the learning ability of students in normal versus virtual reality (VR) watching of videos by mathematical analysis of electroencephalogram (EEG) signals. We played six videos in the 2D and 3D modes for nine subjects and calculated the Shannon entropy of recorded EEG signals to investigate how much their embedded information changes between these modes. We also calculated the Hurst exponent of EEG signals to compare the changes in the memory of signals. The analysis results showed that watching the videos in a VR condition causes greater information and memory in EEG signals. A strong correlation was obtained between the increment of information and memory of EEG signals. These increments also have been verified based on the answers that subjects gave to the questions about the content of videos. Therefore, we can say that when subjects watch a video in a VR condition, more information is transferred to their brains that cause increments in their memory.

scholarly journals Exploring Drugbank in Virtual Reality Chemical Space

2018 ◽  
Author(s):  
Daniel Probst ◽  
Jean-Louis Reymond
Keyword(s):  
Virtual Reality ◽  
Virtual Environments ◽  
Chemical Space ◽  
3D Visualization ◽  
Low Cost ◽  
Natural Extension ◽  
Web Based ◽  
3D Engine ◽  
Abstract Data ◽  
2D And 3D

The recent general availability of low-cost virtual reality headsets, and accompanying 3D engine support, presents an opportunity to bring the concept of chemical space into virtual environments. While virtual reality applications represent a category of widespread tools in other fields, their use in the visualization and exploration of abstract data such as chemical spaces has been experimental. In our previous work we established the concept of interactive 2D maps of chemical spaces, followed by interactive web-based 3D visualizations, culminating in the interactive web-based 3D visualization of extremely large chemical spaces. Virtual reality chemical spaces are a natural extension of these concepts. As 2D and 3D embeddings, and projections of high-dimensional chemical fingerprint spaces were shown to be valuable tools in chemical space visualization and exploration, existing pipelines of data mining and preparation can be extended to be used in virtual reality applications. Here we present an application based on the Unity engine and the virtual reality toolkit (VRTK), allowing for the interactive exploration of chemical space populated by Drugbank compounds in virtual reality. The source code of the application as well as the most recent build are available on GitHub.

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