Sensor Fusion Based on Strong Tracking Filter for Augmented Reality Registration

Abstract:

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Accurate tracking for Augmented Reality applications is a challenging task. Multi-sensors hybrid tracking generally provide more stable than the effect of the single visual tracking. This paper presents a new tightly-coupled hybrid tracking approach combining vision-based systems with inertial sensor. Based on multi-frequency sampling theory in the measurement data synchronization, a strong tracking filter (STF) is used to smooth sensor data and estimate position and orientation. Through adding time-varying fading factor to adaptively adjust the prediction error covariance of filter, this method improves the performance of tracking for fast moving targets. Experimental results show the efficiency and robustness of this proposed approach.

Info:

Periodical:

Key Engineering Materials (Volumes 467-469)

Edited by:

Dehuai Zeng

Pages:

108-113

DOI:

10.4028/www.scientific.net/KEM.467-469.108

Citation:

X. Y. Li and D. Y. Chen, "Sensor Fusion Based on Strong Tracking Filter for Augmented Reality Registration", Key Engineering Materials, Vols. 467-469, pp. 108-113, 2011

Online since:

February 2011

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Price:

$35.00

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