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。
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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