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Walter Meiss

dblp:272/7439 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—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.

Computer graphics and multimedia
1 paper
Virtual and augmented reality · 50% Computer animation and physical simulation · 50%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality › virtual reality
virtual reality applications
0.412020
Exertion-aware path generation · ACM Trans. Graph. 2020

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

optimization · 0.4
YearPublicationVenuePosition
2020 Exertion-aware path generation
abstract
We propose a novel approach for generating paths with desired exertion properties, which can be used for delivering highly realistic and immersive virtual reality applications that help users achieve exertion goals. Given a terrain as input, our optimization-based approach automatically generates feasible paths on the terrain which users can bike to perform body training in virtual reality. The approach considers exertion properties such as the total work and the perceived level of path difficulty in generating the paths. To verify our approach, we applied it to generate paths on a variety of terrains with different exertion targets and constraints. To conduct our user studies, we built an exercise bike whose force feedback was controlled by the elevation angle of the generated path over the terrain. Our user study results showed that users found exercising with our generated paths in virtual reality more enjoyable compared to traditional exercising approaches. Their energy expenditure in biking the generated paths also matched with the specified targets, validating the efficacy of our approach.
Wanwan Li, Biao Xie, Walter Meiss, Haikun Huang, Lap-Fai Yu
ACM Trans. Graph.4