2019
DOI: 10.20870/ijvr.2019.19.3.2917
|View full text |Cite
|
Sign up to set email alerts
|

Controller-based Text-input Techniques for Virtual Reality: An Empirical Comparison

Abstract: Existing consumer VR systems support text input using handheld controllers in combination with virtual keyboards and many designers have attempted to build on these widely used techniques. However, information on current and well-established VR text-input techniques is lacking. In this work, we conduct a comparative empirical evaluation of four controller-based VR text-input techniques, namely, raycasting, drum-like keyboard, head-directed input, and split keyboard. We focus on their text-entry rate and accura… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

2
35
0
2

Year Published

2020
2020
2024
2024

Publication Types

Select...
4
2
2
1

Relationship

0
9

Authors

Journals

citations
Cited by 32 publications
(40 citation statements)
references
References 34 publications
2
35
0
2
Order By: Relevance
“…Text input has been extensively studied. For an in-depth exploration of previous interfaces and how their performance compares, see Dube and Arif's 2019 survey [15], Speicher et al 's 2018 selectionbased text entry comparison [50], or Boletsis and Kongsvig's controller-based comparison [5]. Here, we present an overview of the predominant interface types and a discussion of the most relevant pen-based text input techniques.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Text input has been extensively studied. For an in-depth exploration of previous interfaces and how their performance compares, see Dube and Arif's 2019 survey [15], Speicher et al 's 2018 selectionbased text entry comparison [50], or Boletsis and Kongsvig's controller-based comparison [5]. Here, we present an overview of the predominant interface types and a discussion of the most relevant pen-based text input techniques.…”
Section: Related Workmentioning
confidence: 99%
“…Phrase sets for evaluating text input techniques fall into two categories: (1) simple sentences containing only single-case alphabetical letters or spaces, or (2) complex sentences mixing case and including numbers or more complex symbols. Although all interfaces tested include the ability for complex sentences, we chose to evaluate using only simple sentences to facilitate comparison with other recent VR text input studies that do likewise [5,41,50,56]. Based on the commonly used Mackenzie phrase set [38], 36 simple sentences were chosen at random.…”
Section: Phrase Setmentioning
confidence: 99%
“…First, there is a need to compare the effects that each interaction method has on learning and performance systemically, in addition to user preferences. Although some of this research has found that performance is related to subjective ratings such as naturalness, usability, and preference (Ali & Cardona-Rivera, 2020;Almeida et al, 2019;Boletsis & Stian, 2019;Gusai et al, 2017;Kharoub et al, 2019), it is challenging to draw strong conclusions because the tasks, the types of controllers, and measures of performance vary so widely. Second, there have been few studies that have included multiple types of controllerbased interactions and compared them to more natural VR interactions.…”
Section: Introductionmentioning
confidence: 99%
“…However its results have pointed towards interesting research directions. Future iterations may delve deeper into participants typing proficiency and learning 414 curve using these paradigms [42][43][44], comparing novice typists with expert typists. Another approach may inquire further on the utility of such text input 416 paradigm for people unable to grasp HCs (e.g.…”
mentioning
confidence: 99%