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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 4/2017

11-01-2016 | Original Article

Position stabilisation and lag reduction with Gaussian processes in sensor fusion system for user performance improvement

Authors: Shimin Feng, Roderick Murray-Smith, Andrew Ramsay

Published in: International Journal of Machine Learning and Cybernetics | Issue 4/2017

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Abstract

In this paper we present a novel Gaussian Process (GP) prior model-based sensor fusion approach to dealing with position uncertainty and lag in a system composed of an external position sensing device (Kinect) and inertial sensors embedded in a mobile device for user performance improvement. To test the approach, we conducted two experiments: (1) GPs sensor fusion simulation. Experimental results show that the novel GP sensor fusion helps improve the accuracy of position estimation, and reduce the lag (0.11 s). (2) User study on a trajectory-based target acquisition task in a spatially aware display application. We implemented the real-time sensor fusion system by augmenting the Kinect with a Nokia N9. In the trajectory-based interaction experiment, each user performed target selection tasks following a trajectory in (a) the Kinect system and (b) the sensor fusion system. In comparison with the Kinect time-delay system, our system enables the user to perform the task easier and faster. The MSE of target selection was reduced by 38.3 % and the average task completion time was reduced by 26.7 %.
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Footnotes
2
In this implementation a fixed rotation matrix between the phone body frame and the Kinect frame is assumed.
 
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Metadata
Title
Position stabilisation and lag reduction with Gaussian processes in sensor fusion system for user performance improvement
Authors
Shimin Feng
Roderick Murray-Smith
Andrew Ramsay
Publication date
11-01-2016
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 4/2017
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-015-0488-5

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