Demo Data from EDBT 2026 / reviewers in the wild / expert
Ulrich Steinhoff
dblp:88/1497
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · unresolved
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.
| Computer networks
1 paper |
Wireless sensing and localization · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Wearable and physiological sensing · 77% Ubiquitous computing and smart environments · 23% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless sensing and localization › navigation
dead reckoning |
0.1 | 1 | 2010 | Dead reckoning from the pocket - An experimental study · PerCom 2010 |
Wireless sensing and localization
indoor localization |
0.1 | 1 | 2010 | Dead reckoning from the pocket - An experimental study · PerCom 2010 |
Methods — techniques the papers use, named apart from their topics
inertial sensing · 0.2experimental study · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Dead reckoning from the pocket - An experimental studyabstractModern mobile phones enable absolute positioning based on GPS or WiFi. However, incremental positioning based on dead reckoning is an interesting source of complementary information, e.g., for indoor positioning or for filling in reception gaps. In the literature however, reasonable dead reckoning accuracies have been reported for fixed and typically a priori known device placements only, e.g., on the hip. Therefore, this paper contributes an experimental study of several published as well as novel approaches for dead reckoning in a scenario with unconstrained placement of a device in the user's trouser pockets. Utilizing the movement of a sensor in a trouser pocket due to body motion, we estimate the user's walking direction and steps robustly for arbitrary placements in the pocket and without additional body-worn sensors. We evaluate these methods on a large dataset of 23 traces of 8 different persons, and compare different approaches. Ulrich Steinhoff, Bernt Schiele |
PerCom | 1 |