Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Alan Bränzel

dblp:128/9250 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Interaction techniques and input › input sensing › tracking
pose tracking
0.212013
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
0.212013
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
YearPublicationVenuePosition
2013 GravitySpace: tracking users and their poses in a smart room using a pressure-sensing floor
abstract
We 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
CHI1