Human pose estimation from pressure sensor data

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.