No-model Tracking by Data-driven Method using BP Networks

被引：0
|
作者：
Jin Xue-bo [1 ]
He Hai-ran [1 ]
Wang Ya-ming [1 ]
Yuan Meng-yang [2 ]
机构：
[1] Zhejiang Sci Tech Univ, Coll Informat & Elect, Hangzhou, Zhejiang, Peoples R China
[2] SIAS Int Univ, Coll Informat & Elect, Zhengzhou, Peoples R China
来源：
2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL I | 2010年
基金：
中国国家自然科学基金;
关键词：
model-driven tracking; data-driven tracking; Kalman filter; BP net; video tracking; APPLICATION SIMULATIONS; APPLICATIONS SYSTEMS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In the model-driven tracking approach, the tracking performance is mainly based on the system model. But the accurate model is difficult to obtain, while data-driven tracking approach can't depend on the accuracy of system model and it can tracking by the measurement data. This paper use BP net to develop a data-driven tracking. The BP net is trained by system measurement and prediction get by Kalman filter and the tracking as the output data. The simulation has shown that the data-driven tracking by BP net can obtain good performance even when the moving target is different.
引用
收藏
页码：314 / 317
页数：4
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