Supervised Learning for Yaw Orientation Estimation

Feigl T, Mutschler C, Philippsen M (2018)

Publication Language: English

Publication Status: Accepted

Publication Type: Conference contribution, Conference Contribution

Future Publication Type: Other publication type

Publication year: 2018

Publisher: IEEE Xplore

Conference Proceedings Title: Proceedings of the 9th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2018)

Event location: Nantes FR

ISBN: 978-1-5386-5635-8

URI: https://www2.cs.fau.de/publication/download/IPIN2018a.pdf

DOI: 10.1109/IPIN.2018.8533811

Abstract

With free movement and multi-user capabilities, there is demand to open up Virtual Reality (VR) for large spaces. However, the cost of accurate camera-based tracking grows with the size of the space and the number of users. No-pose (NP) tracking is cheaper, but so far it cannot accurately and stably estimate the yaw orientation of the user’s head in the long-run.

Our novel yaw orientation estimation combines a single inertial sensor located at the human’s head with inaccurate positional tracking. We exploit that humans tend to walk in their viewing direction and that they also tolerate some orientation drift. We classify head and body motion and estimate heading drift to enable low-cost long-time stable head orientation in NP tracking on 100 m × 100 m. Our evaluation shows that we estimate heading reasonably well.

Authors with CRIS profile

Tobias Feigl Lehrstuhl für Informatik 2 (Programmiersysteme) Christopher Mutschler Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics) Michael Philippsen Lehrstuhl für Informatik 2 (Programmiersysteme)

Additional Organisation(s)

Machine Learning and Data Analytics Lab

Related research project(s)

Recurrent Neuronal Networks (RNNs) for Real-Time Estimation of Nonlinear Motion Models (RuNN) Oct. 1, 2017 - March 31, 2021

How to cite

APA:

Feigl, T., Mutschler, C., & Philippsen, M. (2018). Supervised Learning for Yaw Orientation Estimation. In Proceedings of the 9th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2018). Nantes, FR: IEEE Xplore.

MLA:

Feigl, Tobias, Christopher Mutschler, and Michael Philippsen. "Supervised Learning for Yaw Orientation Estimation." Proceedings of the 9th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2018), Nantes IEEE Xplore, 2018.

BibTeX: Download