Demo Data from VLDB 2026 / reviewers in the wild / expert
Cole Hoffbauer
dblp:240/7181
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 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.
| Human-computer interaction and pervasive computing
1 paper |
Immersive interaction · 77% Human-robot interaction · 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 locomotion
redirected walking |
0.4 | 1 | 2019 | Multi-User Redirected Walking and Resetting Using Artificial Potential Fields · IEEE Trans. Vis. Comput. Graph. 2019 |
Human-robot interaction › robot navigation
collision avoidance |
0.1 | 1 | 2019 | Multi-User Redirected Walking and Resetting Using Artificial Potential Fields · IEEE Trans. Vis. Comput. Graph. 2019 |
Methods — techniques the papers use, named apart from their topics
user study · 0.4simulation · 0.4artificial potential field · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Multi-User Redirected Walking and Resetting Using Artificial Potential FieldsabstractHead-mounted displays (HMDs) and large area position tracking systems can enable users to navigate virtual worlds through natural walking. Redirected walking (RDW) imperceptibly steers immersed users away from physical world obstacles allowing them to explore unbounded virtual worlds while walking in limited physical space. In cases of imminent collisions, resetting techniques can reorient them into open space. This work introduces categorically new RDW and resetting algorithms based on the use of artificial potential fields that "push" users away from obstacles and other users. Data from human subject experiments indicate that these methods reduce potential single-user resets by 66% and increase the average distance between resets by 86% compared to previous techniques. A live multi-user study demonstrates the viability of the algorithm with up to 3 concurrent users, and simulation results indicate that the algorithm scales efficiently up to at least 8 users and is effective with larger groups. Eric R. Bachmann, Eric Hodgson, Cole Hoffbauer, Justin Messinger |
IEEE Trans. Vis. Comput. Graph. | 3 |