Object Tracking Based on Cost Sensitive Structured SVM

Guanglin YUAN; Ziwen SUN; Xiaoyan QIN; Liang XIA; Hong ZHU

doi:10.11999/JEIT200708

Volume 43 Issue 11

Nov. 2021

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Guanglin YUAN, Ziwen SUN, Xiaoyan QIN, Liang XIA, Hong ZHU. Object Tracking Based on Cost Sensitive Structured SVM[J]. Journal of Electronics & Information Technology, 2021, 43(11): 3335-3341. doi: 10.11999/JEIT200708

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Guanglin YUAN, Ziwen SUN, Xiaoyan QIN, Liang XIA, Hong ZHU. Object Tracking Based on Cost Sensitive Structured SVM[J]. Journal of Electronics & Information Technology, 2021, 43(11): 3335-3341. doi: 10.11999/JEIT200708

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Object Tracking Based on Cost Sensitive Structured SVM

doi: 10.11999/JEIT200708

Department of Information Engineering of PLA Army Academy of Artillery and Air Defense, Hefei 230031, China

Funds: Anhui Provincial Natural Science Foundation (2008085QF325)

Received Date: 2020-08-10
Rev Recd Date: 2021-04-14

Available Online: 2021-07-11

Publish Date: 2021-11-23

Abstract

Abstract

Object tracking based on structured SVM attracts much attention due to its excellent performance. However, the existing methods have the problem of imbalance between positive and negative samples. To solve the problem, a cost sensitive structured SVM model is proposed for object tracking. Secondly, an algorithm for the proposed model is designed via dual coordinate descent principle. Finally, a multi-scale object tracking method is implemented using the proposed cost sensitive structured SVM. The experimental results on OTB100 datasets and VOT2019 datasets show that compared with the correlation filtering trackers, the proposed method has higher tracking accuracy, and has the advantage of speed compared with the deep object trackers.
- Object tracking,
- Unbalanced problem,
- Cost sensitive,
- Structured SVM

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References(21)

References

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