Application of Unscented Kalman Filter in Tracking of Video Moving Target

被引：1

作者：

Guo, Qin ^{[1
]}

Zeng, Cuixia ^{[1
]}

Jiang, Zhizhao ^{[1
]}

Hu, Xiaotong ^{[1
]}

Deng, Xiaofei ^{[1
]}

机构：

[1] Jishou Univ, Sch Informat Sci & Engn, Jishou 416000, Peoples R China

来源：

BIOMETRIC RECOGNITION (CCBR 2019) | 2019年 / 11818卷

关键词：

Untracked kalman filtering; Trackless transformation; Moving target tracking; Video sequence;

D O I：

10.1007/978-3-030-31456-9_53

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The tracking of video moving target is actually an estimation problem of state variable. Kalman filter method is one of the classical estimators widely used in the field of state estimation. But in tracking system of video moving target, the classical Kalman filtering method has the problem of low tracking accuracy and divergence of filtering. In order to improve the tracking effect, a unscented Kalman filter algorithm is used to track moving target in video sequence. The application of unscented Kalman filter in tracking of video moving target is compared with that of Kalman filter by Matlab simulation software. The results show that unscented Kalman filter is more accurate and better than Kalman filter in tracking of video moving target.

引用

页码：483 / 492

页数：10