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Michael Antonov

dblp:151/9603 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Virtual and augmented reality › tracking
head tracking
0.212014
Head tracking for the Oculus Rift · ICRA 2014
Virtual and augmented reality › tracking
orientation tracking
0.212014
Head tracking for the Oculus Rift · ICRA 2014
Wearable and physiological sensing
inertial sensing
0.212014
Head tracking for the Oculus Rift · ICRA 2014
Immersive interaction
virtual reality interaction
0.112014
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
YearPublicationVenuePosition
2014 Head tracking for the Oculus Rift
abstract
We 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
ICRA4