Algorithm for tracking an infrared single target based on correlation filtering with multi-feature fusion

被引：0
|
作者：
Song J. [1 ]
Miao Q. [1 ]
Shen M. [1 ]
Quan Y. [1 ]
Chen Y. [2 ]
机构：
[1] School of Computer Science and Technology, Xidian University, Xi'an
[2] PLA Unit 96963, Beijing
来源：
Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University | 2019年 / 46卷 / 05期
关键词：
Convolutional networks; Correlation filtering; Infrared target tracking; Multiple features;
D O I：
10.19665/j.issn1001-2400.2019.05.020
中图分类号：
学科分类号：
摘要：
Aiming at the problem of infrared single target tracking, a tracking algorithm based on Multi-feature and correlation filtering is proposed. The algorithm fuses convolution features and differential features. The convolution feature and differential feature are used to train the correlation filtering model, respectively. In the tracking stage, the response graphs obtained from the correlation filtering model of the two features are fused dynamically. The final position of the target is determined by the dynamic fusion response graph, and then the correlation filtering model is updated separately by using the obtained target position. Experiments on the Linköping Thermal InfraRed dataset show that the proposed tracking algorithm has a higher tracking accuracy than the conventional tracking algorithms. © 2019, The Editorial Board of Journal of Xidian University. All right reserved.
引用
收藏
页码：142 / 147
页数：5
相关论文
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