Demo Data from VLDB 2026 / reviewers in the wild / expert
Yoshinobu Yamamoto
dblp:38/5549
· DBLP profile ↗
3ranked-venue papers
0as first author
1since 2021 · last 2021
0000-0002-6082-1391ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 1 since 2021Systems, architecture and hardware · 1Human-computer interaction and ubiquitous computing · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
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 architecture, parallel and distributed computing, and storage systems
1 paper |
Hardware accelerators and domain-specific architectures · 50% Embedded and real-time systems · 50% | |
| Computer graphics and multimedia
1 paper |
Image and video processing · 100% | |
| Artificial intelligence
1 paper |
3D vision · 100% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Embedded and real-time systems › real-time embedded systems › multimedia embedded systems
embedded vision system |
0.1 | 1 | 2006 | Embedded Vision System for Mobile Robot Navigation · ICRA 2006 |
Hardware accelerators and domain-specific architectures
vision accelerator |
0.1 | 1 | 2006 | Embedded Vision System for Mobile Robot Navigation · ICRA 2006 |
Image and video processing › motion estimation
block matching |
0.0 | 1 | 2006 | Embedded Vision System for Mobile Robot Navigation · ICRA 2006 |
Image and video processing › feature extraction
image feature extraction |
0.0 | 1 | 2006 | Embedded Vision System for Mobile Robot Navigation · ICRA 2006 |
Computer vision › 3D vision › 3d scene understanding
spatial relation learning |
0.0 | 1 | 1991 | Learning Spatial Relations from Images · ML 1991 |
Computer vision › 3D vision › 3d scene understanding
spatial relation understanding |
0.0 | 1 | 1991 | Learning Spatial Relations from Images · ML 1991 |
Methods — techniques the papers use, named apart from their topics
systolic array · 0.1dedicated LSI · 0.1DSP · 0.1image-based relation learning · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Proposing Remote Video Conversation System "PARAPPA": Delivering the Gesture and Body Posture with Rotary Screen*abstractGlobalization and the effect of recent infectious disease are changing the remote conversations as a new normal in business meetings, social provision and casual chatting. Previous research show that the remote conversations have a difficulty on showing the presence or attention to the other interlocutors, especially in the situation where the majority of interlocutor share the same place and one or a few interlocutor participate from difference place. This paper proposed "Parappa", a remote video conversation system, for those unbalanced condition by utilizing both physical and virtual approaches to share the nonverbal behaviors of remotely-participating interlocutor. The proposed system is constructed with a rotatable screen which projects the life-size avatar of remote interlocutor. The rotation of the screen represents the body posture and the projected avatar show the gesture. The results of preliminary analyses of eye gaze activities and frequency of the screen rotation during conversation suggests the possibilities that proposed system enables to show the presence of remote interlocutors. Koki Ijuin, Kunihiro Ogata, Kentaro Watanabe, Hiroyasu Miwa, Yoshinobu Yamamoto |
RO-MAN | 5 |
| 2006 | Embedded Vision System for Mobile Robot NavigationabstractWe developed an embedded vision system that can accelerate the basic image processing functions for mobile robot navigation with compact hardware featuring low power consumption. The system is composed of a digital signal processor (DSP) and a dedicated LSI for low-level image processing, specifically for spatial filtering, feature extraction, and block matching operations. The image processing LSI has a dedicated systolic array processor consisting of 64 processing elements to accelerate basic block operations for image feature calculation and correlation-based image matching. The power consumption is only 10 W, about one-seventh that of a typical Pentium 4 personal computer, but the processing speed for correlation matching is roughly three times faster than such a system. With this vision system, we implemented a stereo-vision based navigation algorithm on our mobile service robot and performed a visual navigation experiment in a building hallway Naoyuki Sawasaki, Manabu Nakao, Yoshinobu Yamamoto, Keiju Okabayashi |
ICRA | 3 |
| 1991 | Learning Spatial Relations from Images
Kazuo Hiraki, John H. Gennari, Yoshinobu Yamamoto, Yuichiro Anzai |
ML | 3 |