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Low-cost accurate skeleton tracking based on fusion of kinect and wearable inertial sensors

Destelle, Francois, Ahmadi, Amin, O'Connor, Noel E. orcid logoORCID: 0000-0002-4033-9135, Moran, Kieran orcid logoORCID: 0000-0003-2015-8967, Chatzitofis, Anargyros, Zarpalas, Dimitrios orcid logoORCID: 0000-0002-9649-9306 and Daras, Petros (2014) Low-cost accurate skeleton tracking based on fusion of kinect and wearable inertial sensors. In: 22nd European Signal Processing Conference (EUSIPCO 2014), 1-5 Sept 2014, Lisbon, Portugal.

Abstract
In this paper, we present a novel multi-sensor fusion method to build a human skeleton. We propose to fuse the joint po- sition information obtained from the popular Kinect sensor with more precise estimation of body segment orientations provided by a small number of wearable inertial sensors. The use of inertial sensors can help to address many of the well known limitations of the Kinect sensor. The precise calcu- lation of joint angles potentially allows the quantification of movement errors in technique training, thus facilitating the use of the low-cost Kinect sensor for accurate biomechani- cal purposes e.g. the improved human skeleton could be used in visual feedback-guided motor learning, for example. We compare our system to the gold standard Vicon optical mo- tion capture system, proving that the fused skeleton achieves a very high level of accuracy.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Engineering > Signal processing
Medical Sciences > Sports sciences
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Science and Health > School of Health and Human Performance
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Published in: Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European Signal Processing Conference. .
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:SFI Grant Number 12/RC/2289
ID Code:20596
Deposited On:27 May 2015 13:02 by Kevin Fraser . Last Modified 03 Feb 2023 14:52
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