Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 4
1216-1219,1223

Siamese network object tracking based on hard sample mining

Kang Jie1
Sun Yang1
Shen Junge2
1. College of Electrical & Control Engineering, Shaanxi University of Science & Technology, Xi'an 710021, China
2. Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China
DOI: 10.19734/j.issn.1001-3695.2020.03.0084

Abstract

In complex environment, the object tracking algorithm of fully-convolutional Siamese network is prone to track drift or even track failure. In order to solve the problem, this paper proposed a Siamese network tracking algorithm based on hard sample mining. On the basis of SiamFC, this method first used a feature fusion module for feature fusion to enhance the robustness of feature representation, and then proposed a novel loss function to strengthen the learning ability of network to hard samples and alleviate the problem of imbalance between positive and negative samples. To verify the validity, this method was tested on OTB2015 benchmark and GOT10k dataset. The results of OTB2015 show that this method increases the success rate by 2.6% and the accuracy by 2% compared with SiamFC. On the GOT10k dataset, the mAO of this method is 0.429, which is 3.7% higher than the SiamFC. It proves that this method has a better performance in the case of illumination variation, object deformation, and similar background interference.

Foundation Support

国家自然科学基金资助项目(61603233)
西安市科技计划资助项目(2019216514GXRC001CG002-GXYD1.7)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.03.0084
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 4
Section: Technology of Graphic & Image
Pages: 1216-1219,1223
Serial Number: 1001-3695(2021)04-049-1216-04

Publish History

[2021-04-05] Printed Article

Cite This Article

亢洁, 孙阳, 沈钧戈. 基于难样本挖掘的孪生网络目标跟踪 [J]. 计算机应用研究, 2021, 38 (4): 1216-1219,1223. (Kang Jie, Sun Yang, Shen Junge. Siamese network object tracking based on hard sample mining [J]. Application Research of Computers, 2021, 38 (4): 1216-1219,1223. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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