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Malcolm Hutson

dblp:39/3350 · DBLP profile ↗
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2ranked-venue papers
2as first author
0since 2021 · last 2011
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-authorHuman-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
2 papers
Virtual and augmented reality · 100%
Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 77% User interface design and tools · 23%

Topics — the 5 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality › tracking
head-mounted display tracking
0.222011
JanusVF: Accurate Navigation Using SCAAT and Virtual Fiducials · IEEE Trans. Vis. Comput. Graph. 2011
JanusVF: Accurate Navigation Using SCAAT and Virtual Fiducials · VR 2009
Virtual and augmented reality › tracking
6DOF tracking
0.112011
JanusVF: Accurate Navigation Using SCAAT and Virtual Fiducials · IEEE Trans. Vis. Comput. Graph. 2011
Virtual and augmented reality › tracking
fiducial marker tracking
0.112011
JanusVF: Accurate Navigation Using SCAAT and Virtual Fiducials · IEEE Trans. Vis. Comput. Graph. 2011
Virtual and augmented reality
immersive interaction
0.112009
JanusVF: Accurate Navigation Using SCAAT and Virtual Fiducials · VR 2009
Interaction techniques and input › input sensing
tracking
0.112009
JanusVF: Accurate Navigation Using SCAAT and Virtual Fiducials · VR 2009

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

SCAAT filter · 0.3ARToolkitPlus · 0.3fiducial markers · 0.2
YearPublicationVenuePosition
2011 JanusVF: Accurate Navigation Using SCAAT and Virtual Fiducials
abstract
Several critical limitations exist in the currently available tracking technologies for fully enclosed virtual reality (VR) systems. While several 6DOF tracking projects such as Hedgehog have successfully demonstrated excellent accuracy, precision, and robustness within moderate budgets, these projects still include elements of hardware that can interfere with the user's visual experience. The objective of this project is to design a tracking solution for fully enclosed VR displays that achieves comparable performance to available commercial solutions but without any artifacts that can obscure the user's view. JanusVF is a tracking solution involving a cooperation of both the hardware sensors and the software rendering system. A small, high-resolution camera is worn on the user's head, but faces backward (180 degree rotation about vertical from the user's perspective). After acquisition of the initial state, the VR rendering software draws specific fiducial markers with known size and absolute position inside the VR scene. These virtual markers are only drawn behind the user and in view of the camera. These fiducials are tracked by ARToolkitPlus and integrated by a single-constraint-at-a-time (SCAAT) filter algorithm to update the head pose. Experiments analyzing accuracy, precision, and latency in a six-sided CAVE-like system show performance that is comparable to alternative commercial technologies.
Malcolm Hutson, Dirk Reiners
IEEE Trans. Vis. Comput. Graph.1
2009 JanusVF: Accurate Navigation Using SCAAT and Virtual Fiducials
abstract
Several critical limitations exist in the currently available tracking technologies for fully-enclosed virtual reality (VR) systems. While several 6DOF tracking projects such as Hedgehog [24] have successfully demonstrated excellent accuracy, precision, and robustness within moderate budgets, these projects still include elements of hardware that can interfere with the user's visual experience. The objective of this project is to design a tracking solution for fully-enclosed VR displays that achieves comparable performance to available commercial solutions but without any artifacts that can obscure the user's view. JanusVF is a tracking solution involving a cooperation of both the hardware sensors and the software rendering system. A small, high-resolution camera is worn on the user's head, but faces backwards (180 degree rotation about vertical from the user's perspective). After acquisition of the initial state, the VR rendering software draws specific fiducial markers with known size and absolute position inside the VR scene. These virtual markers are only drawn behind the user and in view of the camera. These fiducials are tracked by ARToolkitPlus [25] and integrated by a single-constraint-at-a-time (SCAAT) [26] filter algorithm to update the head pose. Early experiments in a six-sided CAVE-like system show performance that is comparable to alternative commercial technologies.
Malcolm Hutson, Steven A. White, Dirk Reiners
VR1