Visual vehicle tracking algorithm

被引：4
|
作者：
Lou, JG [1 ]
Tan, TN [1 ]
Hu, WM [1 ]
机构：
[1] Chinese Acad Sci, Inst Automat, NLPR, Beijing 100080, Peoples R China
来源：
ELECTRONICS LETTERS | 2002年 / 38卷 / 18期
关键词：
D O I：
10.1049/el:20020692
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A modified extended Kalman filter (EKF) is proposed for visual vehicle tracking by adding a new objective function to reduce the sensitivity of the filter to model uncertainty. Experimental results show that the performance of this approach is much better than the traditional EKF and its recent variant.
引用
收藏
页码：1024 / 1025
页数：2
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