计算机工程与应用2018，Vol.54Issue(9)：178-182,5.DOI:10.3778/j.issn.1002-8331.1612-0316
改进的核相关滤波跟踪算法
Improved kernelized correlation filter tracking
摘要
Abstract
An improved kernel correlation filtering target tracking algorithm is proposed by Kernelized Correlation Filtering (KCF)tracking algorithm,which can not solve the problem of scale change and out-of-view in target tracking.Firstly,a scale filter is added to improve the target scale change based on training translation filter. In order to solve out-of-view problem, the occlusion processing mechanism is used.When the target is not completely occluded, the SVM is used to train the samples,and the re-detection classifier is adopted to detect.Experimental results show that the tracking accuracy of this method is obviously improved in comparison with other excellent tracking algorithms.关键词
核相关滤波/目标丢失/尺度变化/遮挡/支持向量机Key words
kernel correlation filter/out-of-view/scale change/occlusion/support vector machine分类
信息技术与安全科学引用本文复制引用
孙健,向伟,谭舒昆,刘云鹏..改进的核相关滤波跟踪算法[J].计算机工程与应用,2018,54(9):178-182,5.基金项目
中国科学院国防科技创新重点基金(No.CXJJ-14-Z65). （No.CXJJ-14-Z65）
