Abstract
This paper addresses the problem of gait estimation using visual and inertial data, as well as human motion models. Specifically, a batch least-squares (BLS) algorithm is presented that fuses data from a minimal set of sensors [two inertial measurement units (IMUs), one on each foot, and a head-mounted IMU-camera pair] along with motion constraints corresponding to the different walking states, to estimate the person's head and feet poses. Subsequently, gait models are employed to solve for the lower-body's posture and generate its animation. Experimental results against the VICON motion capture system demonstrate the accuracy of the proposed minimal sensors-based system for determining a person's motion.
| Original language | English (US) |
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| Title of host publication | 2018 IEEE International Conference on Robotics and Automation, ICRA 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 4614-4621 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781538630815 |
| DOIs | |
| State | Published - Sep 10 2018 |
| Event | 2018 IEEE International Conference on Robotics and Automation, ICRA 2018 - Brisbane, Australia Duration: May 21 2018 → May 25 2018 |
Publication series
| Name | Proceedings - IEEE International Conference on Robotics and Automation |
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| ISSN (Print) | 1050-4729 |
Conference
| Conference | 2018 IEEE International Conference on Robotics and Automation, ICRA 2018 |
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| Country/Territory | Australia |
| City | Brisbane |
| Period | 5/21/18 → 5/25/18 |
Bibliographical note
Funding Information:This work was supported by the University of Minnesota and the National Science Foundation (IIS-1328722)
Publisher Copyright:
© 2018 IEEE.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.