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Nick Throm

dblp:216/7500 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—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.

Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 70% Immersive interaction · 30%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Immersive interaction
mixed reality interaction
0.312018
MRTouch: Adding Touch Input to Head-Mounted Mixed Reality · IEEE Trans. Vis. Comput. Graph. 2018
Interaction techniques and input › touch interaction
touch input
0.312018
MRTouch: Adding Touch Input to Head-Mounted Mixed Reality · IEEE Trans. Vis. Comput. Graph. 2018
Interaction techniques and input › touch interaction
touch surface interaction
0.312018
MRTouch: Adding Touch Input to Head-Mounted Mixed Reality · IEEE Trans. Vis. Comput. Graph. 2018
Interaction techniques and input › input sensing › tracking › hand tracking
finger tracking
0.112018
MRTouch: Adding Touch Input to Head-Mounted Mixed Reality · IEEE Trans. Vis. Comput. Graph. 2018

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

surface plane detection and tracking · 0.3infrared camera · 0.3depth camera · 0.3
YearPublicationVenuePosition
2018 MRTouch: Adding Touch Input to Head-Mounted Mixed Reality
abstract
We present MRTouch, a novel multitouch input solution for head-mounted mixed reality systems. Our system enables users to reach out and directly manipulate virtual interfaces affixed to surfaces in their environment, as though they were touchscreens. Touch input offers precise, tactile and comfortable user input, and naturally complements existing popular modalities, such as voice and hand gesture. Our research prototype combines both depth and infrared camera streams together with real-time detection and tracking of surface planes to enable robust finger-tracking even when both the hand and head are in motion. Our technique is implemented on a commercial Microsoft HoloLens without requiring any additional hardware nor any user or environmental calibration. Through our performance evaluation, we demonstrate high input accuracy with an average positional error of 5.4 mm and 95% button size of 16 mm, across 17 participants, 2 surface orientations and 4 surface materials. Finally, we demonstrate the potential of our technique to enable on-world touch interactions through 5 example applications.
Robert Xiao, Julia Schwarz, Nick Throm, Andrew D. Wilson, Hrvoje Benko
IEEE Trans. Vis. Comput. Graph.3