Transformer-based target tracking algorithm for space-based optoelectronic detection

doi:10.3389/fphy.2023.1266927

CIOMP OpenIR

	Transformer-based target tracking algorithm for space-based optoelectronic detection
	R. Zhu, J. Leng, Q. Fu, X. Wang, H. Cai, G. Wen, T. Zhang, H. Shi, Y. Li and H. Jiang
	2023
发表期刊	Frontiers in Physics
ISSN	2296424X
卷号	11
摘要	The target tracking by space-based surveillance systems is difficult due to the long distances, weak energies, fast speeds, high false alarm rates, and low algorithmic efficiencies involved in the process. To mitigate the impact of these difficulties, this article proposes a target tracking algorithm based on image processing and Transformer, which employs a two-dimensional Gaussian soft-thresholding method to reduce the image noise, and combines a Laplace operator-weighted fusion method to augment the image, so as to improve the overall quality of the image and increase the accuracy of target tracking. Based on the SiamCAR framework, the Transformer model in the field of natural language processing is introduced, which can be used to enhance the image features extracted from the backbone network by mining the rich temporal information between the initial and dynamic templates. In order to capture the information of the target’s appearance change in the temporal sequence, a template update branch is introduced at the input of the algorithm, which realizes the dynamic update of the templates by constructing a template memory pool, and selecting the best templates for the candidate templates in the memory pool using the cosine similarity-based selection, thus ensuring the robustness of the tracking algorithm. The experimental results that compared with the SiamCAR algorithm and the mainstream algorithms, the TrD-Siam algorithm proposed in this article effectively improves the tracking success rate and accuracy, addressing poor target tracking performance under space-based conditions, and has a good value of application in the field of optoelectronic detection. Copyright © 2023 Zhu, Leng, Fu, Wang, Cai, Wen, Zhang, Shi, Li and Jiang.
DOI	10.3389/fphy.2023.1266927
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收录类别	sci ; ei
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/68286
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	R. Zhu, J. Leng, Q. Fu, X. Wang, H. Cai, G. Wen, T. Zhang, H. Shi, Y. Li and H. Jiang. Transformer-based target tracking algorithm for space-based optoelectronic detection[J]. Frontiers in Physics,2023,11.
APA	R. Zhu, J. Leng, Q. Fu, X. Wang, H. Cai, G. Wen, T. Zhang, H. Shi, Y. Li and H. Jiang.(2023).Transformer-based target tracking algorithm for space-based optoelectronic detection.Frontiers in Physics,11.
MLA	R. Zhu, J. Leng, Q. Fu, X. Wang, H. Cai, G. Wen, T. Zhang, H. Shi, Y. Li and H. Jiang."Transformer-based target tracking algorithm for space-based optoelectronic detection".Frontiers in Physics 11(2023).

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