Adaptive Tracking Algorithm Based on Modified Strong Tracking Filter

Author(s):  
He You ◽  
Song Qiang ◽  
Dong Yun-long ◽  
Yang Jian
2011 ◽  
Vol 467-469 ◽  
pp. 108-113
Author(s):  
Xin Yu Li ◽  
Dong Yi Chen

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.


2021 ◽  
Vol 30 (6) ◽  
pp. 1152-1158
Author(s):  
SUN Xiaohui ◽  
WEN Tao ◽  
WEN Chenglin ◽  
CHENG Xingshuo ◽  
WU Yunkai

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