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Aman S. Mathur

dblp:167/3718 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-authorArtificial intelligence and machine learning · 1Human-computer interaction and ubiquitous computing · 1 · 1 first-author

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
Learning and educational technologies · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality › virtual environment
immersive virtual environments
0.212015
Low cost virtual reality for medical training · VR 2015
Virtual and augmented reality
medical training
0.212015
Low cost virtual reality for medical training · VR 2015
Learning and educational technologies
simulation-based training
0.112015
Low cost virtual reality for medical training · VR 2015

Methods — techniques the papers use, named apart from their topics

razer hydra · 0.4oculus rift · 0.4
YearPublicationVenuePosition
2016 NRSfM-Flow: Recovering Non-Rigid Scene Flow from Monocular Image Sequences
Vladislav Golyanik, Aman S. Mathur, Didier Stricker
BMVC2
2015 Low cost virtual reality for medical training
abstract
This demo depicts a low cost virtual reality set-up that may be used for medical training and instruction purposes. Using devices such as the Oculus Rift and Razer Hydra, an immersive experience, including hand interactivity can be given. Software running on a PC integrates these devices and presents an interactive and immersive training environment, where trainees are asked to perform a mixed bag of both, simple and complex tasks. These tasks range from identification of certain organs to performing of an actual incision. Trainees learn by doing, albeit in the virtual world. Components of the system are relatively affordable and simple to use, thereby making such a set-up incredibly easy to deploy.
Aman S. Mathur
VR1