Real time tracking of high speed movements in the context of a table tennis application
Proceedings of the ACM symposium on Virtual reality software and technology
An adaptive approach to exponential smoothing for CVE state prediction
Proceedings of the 2nd International Conference on Immersive Telecommunications
Head orientation prediction: delta quaternions versus quaternions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Improved accuracy tracking using synchronized Wiimote cameras
Proceeding of the 16th International Academic MindTrek Conference
| Hi-index | 0.00 |
To enable a user to perform Virtual Reality tasks as efficiently as possible, reducing tracking inaccuracies from noise and latency is crucial. Much work has been done to improve tracking performance by using predictive filtering methods. However, it is unclear what the benefits of each of these methods are in practice, which parameters influence their performance, and what the extent of this influence is. We present an analysis of various orientation prediction and filtering methods using various hand tasks and synthetic signals, and evaluate their performance in relation to each other. We identify critical parameters and analyse their influence on accuracy. Our results show that for the tested datasets, the use of an EKF is sufficient for orientation prediction in VR/AR.