DocumentCode :
1642230
Title :
An analysis of orientation prediction and filtering methods for VR/AR
Author :
Van Rhijn, Arjen ; Van Liere, Robert ; Mulder, Jurriaan D.
Author_Institution :
Center for Math. & Comput. Sci., CWI, Amsterdam, Netherlands
fYear :
2005
Firstpage :
67
Lastpage :
74
Abstract :
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.
Keywords :
Kalman filters; augmented reality; computer vision; filtering theory; gesture recognition; tracking; augmented reality; extended Kalman filters; hand tasks; latency; noise; orientation prediction; predictive filtering methods; synthetic signals; tracking; virtual reality; Computer vision; Delay; Electronic mail; Filtering algorithms; Image processing; Noise reduction; Nonlinear filters; Performance analysis; Signal analysis; Virtual reality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Virtual Reality, 2005. Proceedings. VR 2005. IEEE
Conference_Location :
Bonn
Print_ISBN :
0-7803-8929-8
Type :
conf
DOI :
10.1109/VR.2005.1492755
Filename :
1492755
Link To Document :
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