Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Alex Erendi

dblp:77/995 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2002
—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.

Artificial intelligence
1 paper
3D vision · 100%
Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 100%

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

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision › depth estimation
stereo depth estimation
0.012002
The Use of Dense Stereo Range Data in Augmented Reality · ISMAR 2002
Interaction techniques and input › input sensing › tracking
augmented reality tracking
0.012002
The Use of Dense Stereo Range Data in Augmented Reality · ISMAR 2002
Computer vision › 3D vision › camera pose estimation
camera pose tracking
0.012002
The Use of Dense Stereo Range Data in Augmented Reality · ISMAR 2002
Interaction techniques and input › gesture input
pointing gesture
0.012002
The Use of Dense Stereo Range Data in Augmented Reality · ISMAR 2002

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

fingertip tracking · 0.1dense stereo vision · 0.1camera pose estimation · 0.1
YearPublicationVenuePosition
2002 The Use of Dense Stereo Range Data in Augmented Reality
abstract
This paper describes an augmented reality system that incorporates a real-time dense stereo vision system. Analysis of range and intensity data is used to perform two functions: 1) 3D detection and tracking of the user's fingertip or a pen to provide natural 3D pointing gestures, and 2) computation of the 3D position and orientation of the user's viewpoint without the need for fiducial mark calibration procedures, or manual initialization. The paper describes the stereo depth camera, the algorithms developed for pointer tracking and camera pose tracking, and demonstrates their use within an application in the field of oil and gas exploration.
Gaile G. Gordon, Mark Billinghurst, Melanie Bell, John Woodfill, Bill Kowalik, Alex Erendi, Janet Tilander
ISMAR6