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Wennan He

dblp:252/9406 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2021
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021

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 · 50% Ubiquitous computing and smart environments · 50%
Computer graphics and multimedia
1 paper
Virtual and augmented reality · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Immersive interaction
augmented reality
0.512021
Spatial Anchor Based Indoor Asset Tracking · VR 2021
Virtual and augmented reality
fiducial markers
0.112021
Spatial Anchor Based Indoor Asset Tracking · VR 2021

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

spatial anchors · 1.0fiducial marker tracking · 1.0
YearPublicationVenuePosition
2021 Spatial Anchor Based Indoor Asset Tracking
abstract
Indoor asset tracking is an essential task in many areas of industry such as shipping and warehousing. Widely-used asset tracking technologies typically require supporting infrastructure (signal transponders) to communicate with active tags on the assets. Continuous asset tracking in large indoor spaces like warehouses can be costly, and reliable reference points are needed to calculate asset positions accurately. In this paper, we describe an indoor asset tracking technique for augmented reality (AR) that combines the use of (passive) fiducial markers together with flexible spatial anchors. Our approach, called SABIAT, continuously tracks the approximate location of an asset using spatial anchors and, when needed, the precise location of that asset using fiducial markers. We have applied our SABIAT technique to build a demonstrator system, AR-IPS, to show how assets can be tracked and located inside of a large, multi-level building.
Wennan He, Mingze Xi, Henry J. Gardner, Ben Swift, Matt Adcock
VR1