Human pose estimation from pressure sensor data

Leslie Casas, Chris Mürwald, Felix Achilles, Diana Mateus, Dietrich Huber, Nassir Navab, Stefanie Demirci

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Scopus citations

Abstract

In-bed motion monitoring has become of great interest for a variety of clinical applications. In this paper, we introduce a hashbased learning method to retrieve human poses from pressure sensors data in real time considering temporal correlation between poses. The basis of our approach is a multimodal database describing different in-bed activities. Database entries have been created using an array of pressure sensors and an additional motion capture system. Our results show good performance even in poses where the subject has minimal contact with the sensors.

Original languageEnglish
Title of host publicationInformatik aktuell
EditorsAndreas Maier, Thomas M. Deserno, Heinz Handels, Klaus H. Maier-Hein, Christoph Palm, Thomas Tolxdorff
PublisherSpringer Science and Business Media Deutschland GmbH
Pages285-290
Number of pages6
ISBN (Print)9783540295945, 9783540748366, 9783540853237, 9783642246579, 9783642337062, 9783642413087, 9783662451083, 9783662557846, 9783662565360, 9783662580950
DOIs
StatePublished - 2018
EventWorkshop on Bildverarbeitung fur die Medizin, 2018 - Erlangen, Germany
Duration: 11 Mar 201813 Mar 2018

Publication series

NameInformatik aktuell
Volume0
ISSN (Print)1431-472X

Conference

ConferenceWorkshop on Bildverarbeitung fur die Medizin, 2018
Country/TerritoryGermany
CityErlangen
Period11/03/1813/03/18

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