Demo Data from EDBT 2026 / reviewers in the wild / expert
Yoichi Motokawa
dblp:58/3336
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2006
—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-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
1 paper |
Virtual and augmented reality · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Learning and educational technologies · 100% | |
| Artificial intelligence
1 paper |
3D vision · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Virtual and augmented reality
augmented reality |
0.1 | 1 | 2006 | Support system for guitar playing using augmented reality display · ISMAR 2006 |
Virtual and augmented reality
visual guidance |
0.1 | 1 | 2006 | Support system for guitar playing using augmented reality display · ISMAR 2006 |
Learning and educational technologies › immersive learning
augmented reality learning |
0.1 | 1 | 2006 | Support system for guitar playing using augmented reality display · ISMAR 2006 |
Computer vision › 3D vision › pose estimation
pose tracking |
0.0 | 1 | 2006 | Support system for guitar playing using augmented reality display · ISMAR 2006 |
Methods — techniques the papers use, named apart from their topics
natural feature tracking · 0.2marker-based tracking · 0.2edge detection · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2006 | Support system for guitar playing using augmented reality displayabstractLearning to play the guitar is difficult. We proposed a system that assists people learning to play the guitar using augmented reality. This system shows a learner how to correctly hold the strings by overlaying a virtual hand model and lines onto a real guitar. The player learning to play the guitar can easily understand the required position by overlapping their hand on a visual guide. An important issue for this system to address is the accurate registration between the visual guide and the guitar, therefore we need to track the pose and the position of the guitar. We also proposed a method to track the guitar with a visual marker and natural features of the guitar. Since we used marker information and edge information as natural features, the system could continually track the guitar. Accordingly, our system can constantly display visual guides at the required position to enable a player to learn to play the guitar in a natural manner. Yoichi Motokawa, Hideo Saito 0001 |
ISMAR | 1 |