Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

L. Casas, C. Muerwald, F. Achilles, D. Mateus, D. Huber, N. Navab, S. Demirci
Human Pose Estimation from Pressure Sensor Data
Bildverarbeitung fuer die Medizin 2018, pp 285-290 (bib)

In-bed motion monitoring has become of great interest for a variety of clinical applications. In this paper, we introduce a hash- based 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.
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