Demo Data from SIGIR 2026 / reviewers in the wild / expert
Christoph Birgmann
dblp:292/6425
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 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
1 paper |
Immersive interaction · 77% Interaction techniques and input · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Immersive interaction
virtual reality interaction |
0.5 | 1 | 2021 | Exploring Input Approximations for Control Panels in Virtual Reality · VR 2021 |
Interaction techniques and input › input device
controller-based interaction |
0.1 | 1 | 2021 | Exploring Input Approximations for Control Panels in Virtual Reality · VR 2021 |
Methods — techniques the papers use, named apart from their topics
user study · 0.5framework for interactive fidelity analysis · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Exploring Input Approximations for Control Panels in Virtual RealityabstractToday's availability of sophisticated consumer-grade Virtual Reality (VR) hardware provides affordable access to training simulation technology. In contrast to more traditional high fidelity training simulations utilizing physical replicas of control panels that allow natural interaction, users of virtual training often rely on handheld VR controllers to manipulate simulated controls. Therefore, control manipulations of virtual buttons and sliders must be mapped to approximations of real hand manipulations. For instance, the turning of a physical knob with thumb and index finger can be mapped to a gross motor forearm rotation, or a fine motor joystick manipulation when manipulating a controller. In this paper, we present an exploration of hand input approximations of real hands to manipulate the buttons, toggles, knobs and sliders using typical handheld VR controllers. We use common Oculus Quest controllers that rely on capacitive sensing to create basic, approximate hand gestures. We demonstrate the potential of our designs by performing an experiment in which we compare approximate hand gestures against using the controller's joystick that allows fine motor control using thumb input, and a baseline ray-casting interaction that is commonly used in VR applications. We provide a detailed analysis of our interaction designs using the Framework for Interactive Fidelity Analysis (FIFA), which allows us to discuss differences between input approximations and the real-world hand manipulations. Markus Tatzgern, Christoph Birgmann |
VR | 2 |