In nonlinear systems, the fusion algorithm based on extended Kalman Filter suffers from the disadvantage that the tracking precision is not satisfied.
在非线性系统中,常用的跟踪滤波算法是基于扩展的卡尔曼滤波算法的融合算法,但是这种融合算法的跟踪精度并不是很高。
Experiments show that the new algorithm has good recognition precision and realtime tracking performance, and can adapt to the application requirements of augmenting reality systems.
实验表明,识别算法具有较好的跟踪精度和实时性,能够满足增强现实系统的应用要求。
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