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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.; Moran, Kieran; Chatzitofis, Anargyros; Zarpalas, Dimitrios; Daras, Petros
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.
Keyword(s): Signal processing; Sports sciences
Publication Date:
2014
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Destelle, Francois, Ahmadi, Amin, O'Connor, Noel E. ORCID: 0000-0002-4033-9135 <https://orcid.org/0000-0002-4033-9135>, Moran, Kieran ORCID: 0000-0003-2015-8967 <https://orcid.org/0000-0003-2015-8967>, Chatzitofis, Anargyros, Zarpalas, Dimitrios 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.
File Format(s): application/pdf
Related Link(s): http://doras.dcu.ie/20596/1/EUSIPCO-Final2014.pdf
First Indexed: 2015-05-28 05:05:08 Last Updated: 2019-02-09 06:23:05