Demo Data from EDBT 2026 / reviewers in the wild / expert
Matt Longest
dblp:264/7663
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2024
0009-0004-8803-4535ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
2 papers |
Interaction techniques and input · 100% | |
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Interaction techniques and input
text entry |
1.4 | 2 | 2024 | Efficient Mid-Air Text Input Correction in Virtual Reality · ISMAR 2024 Evaluating the Performance of Hand-Based Probabilistic Text Input Methods on a Mid-Air Virtual Qwerty Keyboard · IEEE Trans. Vis. Comput. Graph. 2023 |
Virtual and augmented reality › immersive interaction
text input |
0.8 | 1 | 2024 | Efficient Mid-Air Text Input Correction in Virtual Reality · ISMAR 2024 |
Virtual and augmented reality
virtual reality |
0.8 | 1 | 2024 | Efficient Mid-Air Text Input Correction in Virtual Reality · ISMAR 2024 |
Interaction techniques and input › text entry
text correction |
0.8 | 1 | 2024 | Efficient Mid-Air Text Input Correction in Virtual Reality · ISMAR 2024 |
Interaction techniques and input › text entry
virtual reality text entry |
0.2 | 1 | 2023 | Evaluating the Performance of Hand-Based Probabilistic Text Input Methods on a Mid-Air Virtual Qwerty Keyboard · IEEE Trans. Vis. Comput. Graph. 2023 |
Methods — techniques the papers use, named apart from their topics
user study · 1.5interaction design · 1.5touch typing · 0.7probabilistic decoding · 0.7hand tracking · 0.7gesture typing · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Efficient Mid-Air Text Input Correction in Virtual RealityabstractThe task of inputting text within virtual reality has attracted significant research attention over the last five years. Less well explored is the related task of correcting inputted text when errors are made. This is despite the fact that considerable time and frustration stems from efforts to correct text. In this paper, we bridge this gap in prior research and explore efficient methods for supporting text input correction in virtual reality. We present a characterization of the types and frequencies of errors encountered when inputting text in virtual reality and an analysis of effective editing strategies. We also present the results of a user study evaluating the performance and usability trade-offs for several interaction methods leveraging the unique capabilities of modern head-mounted displays. John J. Dudley, Amy Karlson, Kashyap Todi, Hrvoje Benko, Matt Longest, Robert Wang 0002, Per Ola Kristensson |
ISMAR | 5 |
| 2023 | Evaluating the Performance of Hand-Based Probabilistic Text Input Methods on a Mid-Air Virtual Qwerty KeyboardabstractIntegrated hand-tracking on modern virtual reality (VR) headsets can be readily exploited to deliver mid-air virtual input surfaces for text entry. These virtual input surfaces can closely replicate the experience of typing on a Qwerty keyboard on a physical touchscreen, thereby allowing users to leverage their pre-existing typing skills. However, the lack of passive haptic feedback, unconstrained user motion, and potential tracking inaccuracies or observability issues encountered in this interaction setting typically degrades the accuracy of user articulations. We present a comprehensive exploration of error-tolerant probabilistic hand-based input methods to support effective text input on a mid-air virtual Qwerty keyboard. Over three user studies we examine the performance potential of hand-based text input under both gesture and touch typing paradigms. We demonstrate typical entry rates in the range of 20 to 30 wpm and average peak entry rates of 40 to 45 wpm. John J. Dudley, Jingyao Zheng, Aakar Gupta, Hrvoje Benko, Matt Longest, Robert Wang 0002, Per Ola Kristensson |
IEEE Trans. Vis. Comput. Graph. | 5 |