CIOMP OpenIR
A template consensus method for visual tracking
T.-x.Zhou; D.-d.Zeng; M.Zhu; A.Kuijper
2019
发表期刊Optoelectronics Letters
ISSN16731905
卷号15期号:1页码:70-74
摘要Visual tracking is a challenging problem in computer vision. Recently, correlation filter-based trackers have shown to provide excellent tracking performance. Inspired by a sample consensus approach proposed for foreground detection, which classifies a given pixel as foreground or background based on its similarity to recently observed samples, we present a template consensus tracker based on the kernelized correlation filter (KCF). Instead of keeping only one target appearance model in the KCF, we make a feature pool to keep several target appearance models in our method and predict the new target position by searching for the location of the maximal value of the response maps. Both quantitative and qualitative evaluations are performed on the CVPR2013 tracking benchmark dataset. The results show that our proposed method improves the original KCF tracker by 8.17% in the success plot and 8.11% in the precision plot. 2019, Tianjin University of Technology and Springer-Verlag GmbH Germany, part of Springer Nature.
关键词Optoelectronic devices,Magnetic materials
DOI10.1007/s11801-019-8109-2
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收录类别EI
语种英语
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文献类型期刊论文
条目标识符http://ir.ciomp.ac.cn/handle/181722/62729
专题中国科学院长春光学精密机械与物理研究所
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T.-x.Zhou,D.-d.Zeng,M.Zhu,et al. A template consensus method for visual tracking[J]. Optoelectronics Letters,2019,15(1):70-74.
APA T.-x.Zhou,D.-d.Zeng,M.Zhu,&A.Kuijper.(2019).A template consensus method for visual tracking.Optoelectronics Letters,15(1),70-74.
MLA T.-x.Zhou,et al."A template consensus method for visual tracking".Optoelectronics Letters 15.1(2019):70-74.
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