Demo Data from EDBT 2026 / reviewers in the wild / expert
Michael Antonov
dblp:151/9603
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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 |
Wearable and physiological sensing · 77% Immersive interaction · 23% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality › tracking
head tracking |
0.2 | 1 | 2014 | Head tracking for the Oculus Rift · ICRA 2014 |
Virtual and augmented reality › tracking
orientation tracking |
0.2 | 1 | 2014 | Head tracking for the Oculus Rift · ICRA 2014 |
Wearable and physiological sensing
inertial sensing |
0.2 | 1 | 2014 | Head tracking for the Oculus Rift · ICRA 2014 |
Immersive interaction
virtual reality interaction |
0.1 | 1 | 2014 | Head tracking for the Oculus Rift · ICRA 2014 |
Methods — techniques the papers use, named apart from their topics
sensor fusion · 0.4predictive tracking · 0.4dead reckoning compensation · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Head tracking for the Oculus RiftabstractWe present methods for efficiently maintaining human head orientation using low-cost MEMS sensors. We particularly address gyroscope integration and compensation of dead reckoning errors using gravity and magnetic fields. Although these problems have been well-studied, our performance criteria are particularly tuned to optimize user experience while tracking head movement in the Oculus Rift Development Kit, which is the most widely used virtual reality headset to date. We also present novel predictive tracking methods that dramatically reduce effective latency (time lag), which further improves the user experience. Experimental results are shown, along with ongoing research on positional tracking. Steven M. LaValle, Anna Yershova, Max Katsev, Michael Antonov |
ICRA | 4 |