Object Tracking Based on Kernel Recursive Least-Squares with Total Firror Rate Minimization

被引：0

作者：

Jang, Se-In ^{[1
]}

Oh, Kangrok ^{[1
]}

Teoh, Andrew Beng Jin ^{[1
]}

Toh, Kar-Ann ^{[1
]}

机构：

[1] Yonsei Univ, Sch Elect & Elect Engn, Seoul 120749, South Korea

来源：

PROCEEDINGS OF THE 2013 IEEE 8TH CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA) | 2013年

关键词：

D O I：

暂无

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：

This paper presents an online tracking system which considers both target appearance and background changes simultaneously. Based on a kernel technique, a recursive formulation is proposed for total-error-rate (TER) minimization. Subsequently:, the online solution is integrated into particle filtering to effectively distinguish the target object from the background. Our system is compared qualitatively and quantitatively with related existing methods on publicly available video sequences.

引用

页码：1415 / 1419

页数：5

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