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Daniel Sugarman

dblp:24/11181 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 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 · 100%
Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 100%

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

TopicWeightPapersLastEvidence papers
Virtual and augmented reality › navigation
3d navigation
0.112012
NuNav3D: A touch-less, body-driven interface for 3D navigation · VR 2012
Virtual and augmented reality
immersive interaction
0.112012
NuNav3D: A touch-less, body-driven interface for 3D navigation · VR 2012
Interaction techniques and input
gesture input
0.012012
NuNav3D: A touch-less, body-driven interface for 3D navigation · VR 2012

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

user study · 0.3depth sensor pose recognition · 0.3
YearPublicationVenuePosition
2012 NuNav3D: A touch-less, body-driven interface for 3D navigation
abstract
We introduce NuNav3D, a body-driven 3D navigation interface for large displays and immersive scenarios. While 3D navigation is a core component of VR applications, certain situations, like remote displays in public or large visualization environments, do not allow for using a navigation controller or prop. NuNav3D maps hand motions, obtained from a pose recognition framework which is driven by a depth sensor, to a virtual camera manipulator, allowing for direct control of 4 DOFs of navigation. We present the NuNav3D navigation scheme and our preliminary user study results under two scenarios, a path-following case with tight geometrical constraints and an open space exploration case, while comparing our method against a traditional joypad controller.
Charilaos Papadopoulos, Daniel Sugarman, Arie E. Kaufman
VR2