Human pose estimation from pressure sensor data
Casas L, Mürwald C, Achilles F, Mateus D, Huber D, Navab N, Demirci S (2018)
Publication Type: Conference contribution
Publication year: 2018
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 0
Pages Range: 285-290
Conference Proceedings Title: Informatik aktuell
Event location: Erlangen, DEU
ISBN: 9783540295945
DOI: 10.1007/978-3-662-56537-7_77
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.
Involved external institutions
Germany (DE)
Austria (AT)How to cite
APA:
Casas, L., Mürwald, C., Achilles, F., Mateus, D., Huber, D., Navab, N., & Demirci, S. (2018). Human pose estimation from pressure sensor data. In Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus H. Maier-Hein, Christoph Palm, Thomas Tolxdorff (Eds.), Informatik aktuell (pp. 285-290). Erlangen, DEU: Springer Science and Business Media Deutschland GmbH.
MLA:
Casas, Leslie, et al. "Human pose estimation from pressure sensor data." Proceedings of the Workshop on Bildverarbeitung fur die Medizin, 2018, Erlangen, DEU Ed. Andreas Maier, Thomas M. Deserno, Heinz Handels, Klaus H. Maier-Hein, Christoph Palm, Thomas Tolxdorff, Springer Science and Business Media Deutschland GmbH, 2018. 285-290.
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