Stochastic optimal control: theory and application
Stochastic optimal control: theory and application
On temporal-spatial realism in the virtual reality environment
UIST '91 Proceedings of the 4th annual ACM symposium on User interface software and technology
Improving static and dynamic registration in an optical see-through HMD
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
A 3D tracking experiment on latency and its compensation methods in virtual environments
Proceedings of the 8th annual ACM symposium on User interface and software technology
Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
Double exponential smoothing: an alternative to Kalman filter-based predictive tracking
EGVE '03 Proceedings of the workshop on Virtual environments 2003
Tolerance of Temporal Delay in Virtual Environments
VR '01 Proceedings of the Virtual Reality 2001 Conference (VR'01)
Perceptual Stability During Head Movement in Virtual Reality
VR '02 Proceedings of the IEEE Virtual Reality Conference 2002
Pose and motion estimation from vision using dual quaternion-based extended kalman filtering
Pose and motion estimation from vision using dual quaternion-based extended kalman filtering
An Analysis of Orientation Prediction and Filtering Methods for VR/AR
VR '05 Proceedings of the 2005 IEEE Conference 2005 on Virtual Reality
Predictive head movement tracking using a Kalman filter
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Knowledge visualization for engineered systems
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
Human tracking from a mobile agent: Optical flow and Kalman filter arbitration
Image Communication
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Display lag in simulation environments with helmet-mounted displays causes a loss of immersion that degrades the value of virtual/augmented reality training simulators. Simulators use predictive tracking to compensate for display lag, preparing display updates based on the anticipated head motion. This paper proposes a new method for predicting head orientation using a delta quaternion (DQ)-based extended Kalman filter (EKF) and compares the performance to a quaternion EKF. The proposed framework operates on the change in quaternion between consecutive data frames (the DQ), which avoids the heavy computational burden of the quaternion motion equation. Head velocity is estimated from the DQ by an EKF and then used to predict future head orientation. We have tested the new framework with captured head motion data and compared it with the computationally expensive quaternion filter. Experimental results indicate that the proposed DQ method provides the accuracy of the quaternion method without the heavy computational burden.