Demo Data from SIGIR 2026 / reviewers in the wild / expert
Tomohisa Yoshimi
dblp:75/2646
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1999
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 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.
| Human-computer interaction and pervasive computing
1 paper |
Ubiquitous computing and smart environments · 44% Wearable and physiological sensing · 44% Health and well-being technologies · 13% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Ubiquitous computing and smart environments
pressure distribution sensing |
0.0 | 1 | 1999 | Body Parts Positions and Posture Estimation System Based on Pressure Distribution Image · ICRA 1999 |
Methods — techniques the papers use, named apart from their topics
template matching · 0.0model-based pressure image · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1999 | Body Parts Positions and Posture Estimation System Based on Pressure Distribution ImageabstractWe develop a body parts position and posture estimation system. This system consists of a pressure sensor distributed bed and body parts position and posture estimation software. The computer constructs many pressure distribution images based on the simple human models and accumulates these images to its memory, called the model-based pressure image templates. The pressure distribution image through is compared with model-based pressure image templates to find out the most matched pressure image template. The model-based pressure image templates contain body parts positions and joint angles information, so the body parts position contacting with the bed can easily be estimated by using the most matched model-based pressure image template. Finally, an estimated posture is displayed as a 3D computer graphics image. An experimental result reveals that the system not only can display the estimated lying human posture intuitively, but can also estimate the lying human's body parts position accurately where the body parts contacts with bed. Tatsuya Harada, Taketoshi Mori, Yoshifumi Nishida, Tomohisa Yoshimi, Tomomasa Sato |
ICRA | 4 |