Demo Data from SIGIR 2026 / reviewers in the wild / expert
Alan Bränzel
dblp:128/9250
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2013
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-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.
| Human-computer interaction and pervasive computing
1 paper |
Ubiquitous computing and smart environments · 50% Interaction techniques and input · 50% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Interaction techniques and input › input sensing › tracking
pose tracking |
0.2 | 1 | 2013 | GravitySpace: tracking users and their poses in a smart room using a pressure-sensing floor · CHI 2013 |
Ubiquitous computing and smart environments › ambient intelligence
smart rooms |
0.2 | 1 | 2013 | GravitySpace: tracking users and their poses in a smart room using a pressure-sensing floor · CHI 2013 |
Methods — techniques the papers use, named apart from their topics
system design · 0.2prototype · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2013 | GravitySpace: tracking users and their poses in a smart room using a pressure-sensing floorabstractWe explore how to track people and furniture based on a high-resolution pressure-sensitive floor. Gravity pushes people and objects against the floor, causing them to leave imprints of pressure distributions across the surface. While the sensor is limited to sensing direct contact with the surface, we can sometimes conclude what takes place above the surface, such as users' poses or collisions with virtual objects. We demonstrate how to extend the range of this approach by sensing through passive furniture that propagates pressure to the floor. To explore our approach, we have created an 8 m2 back-projected floor prototype, termed GravitySpace, a set of passive touch-sensitive furniture, as well as algorithms for identifying users, furniture, and poses. Pressure-based sensing on the floor offers four potential benefits over camera-based solutions: (1) it provides consistent coverage of rooms wall-to-wall, (2) is less susceptible to occlusion between users, (3) allows for the use of simpler recognition algorithms, and (4) intrudes less on users' privacy. Alan Bränzel, Christian Holz 0001, Daniel Hoffmann, Dominik Schmidt, Marius Knaust, Patrick Lühne, René Meusel, Stephan Richter 0003, Patrick Baudisch |
CHI | 1 |