Demo Data from EDBT 2026 / reviewers in the wild / expert
Daniel Sugarman
dblp:24/11181
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 1
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.
| Computer graphics and multimedia
1 paper |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Interaction techniques and input · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality › navigation
3d navigation |
0.1 | 1 | 2012 | NuNav3D: A touch-less, body-driven interface for 3D navigation · VR 2012 |
Virtual and augmented reality
immersive interaction |
0.1 | 1 | 2012 | NuNav3D: A touch-less, body-driven interface for 3D navigation · VR 2012 |
Interaction techniques and input
gesture input |
0.0 | 1 | 2012 | NuNav3D: A touch-less, body-driven interface for 3D navigation · VR 2012 |
Methods — techniques the papers use, named apart from their topics
user study · 0.3depth sensor pose recognition · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | NuNav3D: A touch-less, body-driven interface for 3D navigationabstractWe introduce NuNav3D, a body-driven 3D navigation interface for large displays and immersive scenarios. While 3D navigation is a core component of VR applications, certain situations, like remote displays in public or large visualization environments, do not allow for using a navigation controller or prop. NuNav3D maps hand motions, obtained from a pose recognition framework which is driven by a depth sensor, to a virtual camera manipulator, allowing for direct control of 4 DOFs of navigation. We present the NuNav3D navigation scheme and our preliminary user study results under two scenarios, a path-following case with tight geometrical constraints and an open space exploration case, while comparing our method against a traditional joypad controller. Charilaos Papadopoulos, Daniel Sugarman, Arie E. Kaufman |
VR | 2 |