Siamese Object Tracking Based on Key Feature Information Perception and Online Adaptive Masking

HE Zhiwei; NIE Jiahao; DU Chenjie; GAO Mingyu; DONG Zhekang

doi:10.11999/JEIT210296

Volume 44 Issue 5

May 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(5): 1714-1722

HE Zhiwei, NIE Jiahao, DU Chenjie, GAO Mingyu, DONG Zhekang. Siamese Object Tracking Based on Key Feature Information Perception and Online Adaptive Masking[J]. Journal of Electronics & Information Technology, 2022, 44(5): 1714-1722. doi: 10.11999/JEIT210296

Citation:

HE Zhiwei, NIE Jiahao, DU Chenjie, GAO Mingyu, DONG Zhekang. Siamese Object Tracking Based on Key Feature Information Perception and Online Adaptive Masking[J]. Journal of Electronics & Information Technology, 2022, 44(5): 1714-1722. doi: 10.11999/JEIT210296

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Siamese Object Tracking Based on Key Feature Information Perception and Online Adaptive Masking

doi: 10.11999/JEIT210296

HE Zhiwei^{1, 2},
NIE Jiahao^{1, 2},
DU Chenjie^{1, 2
,
,},
GAO Mingyu^{1, 2},
DONG Zhekang^{1, 3}

1.
School of Electronics Information, Hangzhou Dianzi University, Hangzhou 310018, China
2.
Zhejiang Provincial Key Laboratory of Equipment Electronics, Hangzhou 310018, China
3.
Department of Electrical Engineering, The Hong Kong Polytechnic University, HongKong 999077, China

Funds: The National Natural Science Foundation of China (61571394), The Key R&D Program of Zhejiang Province (2020C03098)

Received Date: 2021-04-13
Accepted Date: 2021-11-02
Rev Recd Date: 2021-11-02

Available Online: 2021-12-22

Publish Date: 2022-05-25

Abstract

Abstract

The application of Siamese network to visual object tracking has greatly improved the performance of the tracker recently, which can take both accuracy and speed into account. However, the accuracy of Siamese network tracker is limited to a great extent. In order to solve the above problems, a key information feature perception module based on channel attention mechanism to enhance the discrimination ability of the network model is proposed, which make the network focus on the convolution feature changes of the target; On this basis, an online adaptive masking strategy is proposed, which adaptively masks the subsequent frames according to the output state of the cross-correlation layer learned online, so as to highlight the foreground target. Experiments on OTB100 and GOT-10k datasets show that without affecting the real-time performance, the proposed tracker has a significant improvement in accuracy compared with the benchmark, and has a robust tracking effect in complex scenes such as occlusion, scale change and background clutter.
- Object tracking,
- Siamese network,
- Key feature information perception,
- Adaptive mask

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References(23)

References

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