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Learning salient features to prevent model drift for correlation tracking

文献类型：期刊论文

作者Zhang, Yu1,2; Gao, Xingyu1; Chen, Zhenyu3,4; Zhong, Huicai1; Li, Liang5; Yan, Chenggang6; Shen, Tao7
刊名NEUROCOMPUTING
出版日期2020-12-22
卷号418页码:1-10
关键词Salient features Drift prevention Correlation tracking
ISSN号0925-2312
DOI10.1016/j.neucom.2019.12.006
英文摘要Correlation Filter (CF) based algorithms play an important role in the field of Visual Object Tracking (VOT) due to their high accuracy and low computational complexity. While existing CF tracking algorithms suf-fer performance degradation due to inaccurate object modeling. In this paper, we improve the object modeling accuracy in both CF training stage and target detection procedure to preventing the drift problem. Specifically, we propose a multi-model structure for CF trackers to capture the target appearance changes, where different appearance models are trained with specific samples to catch the salient features of the target and reduce the computational cost. Furthermore, a space filter for detection features is designed to suppress the boundary effect under Gaussian motion prior, which contributes to improving the accuracy of position estimation. We deploy our method to three hand-crafted features based CF trackers to perform real-time visual tracking on popular benchmarks. The experimental results demonstrate the efficacy of our proposed scheme and the efficiency of our trackers. In addition, we provide a comprehensive analysis of the proposed method to facilitate application. (c) 2019 Published by Elsevier B.V.
资助项目National Nature Science Foundation of China[61702491] ; National Nature Science Foundation of China[61771457] ; National Nature Science Foundation of China[61732007]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000589911100001
出版者ELSEVIER
源URL[http://119.78.100.204/handle/2XEOYT63/16073]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Gao, Xingyu; Chen, Zhenyu
作者单位1.Chinese Acad Sci, Inst Microelect, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Microelect, Beijing, Peoples R China
3.State Grid Corp China, Big Data Ctr, Beijing, Peoples R China
4.China Elect Power Res Inst, Beijing, Peoples R China
5.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China
6.Hangzhou Dianzi Univ, Inst Informat & Control, Hangzhou, Peoples R China
7.Kunming Univ Sci & Technol, Sch Informat Engn & Automat, Kunming, Yunnan, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Yu,Gao, Xingyu,Chen, Zhenyu,et al. Learning salient features to prevent model drift for correlation tracking[J]. NEUROCOMPUTING,2020,418:1-10.
APA Zhang, Yu.,Gao, Xingyu.,Chen, Zhenyu.,Zhong, Huicai.,Li, Liang.,...&Shen, Tao.(2020).Learning salient features to prevent model drift for correlation tracking.NEUROCOMPUTING,418,1-10.
MLA Zhang, Yu,et al."Learning salient features to prevent model drift for correlation tracking".NEUROCOMPUTING 418(2020):1-10.

入库方式： OAI收割

来源：计算技术研究所

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