RT Journal Article
SR 00
ID 10.1007/s13042-015-0488-5
A1 Feng, Shimin
A1 Murray-Smith, Roderick
A1 Ramsay, Andrew
T1 Position stabilisation and lag reduction with Gaussian processes in sensor fusion system for user performance improvement
JF International Journal of Machine Learning and Cybernetics
YR 2017
FD 2017-08
VO 8
IS 4
SP 1167
OP 1184
AB 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 %.
PB Springer
SN 1868-8071
LK https://eprints.gla.ac.uk/114818/