Target Tracking Algorithm Based on Adaptive Updating of Multilayer Convolution Features

Mengyuan, 曾梦媛 Zeng; Zhenhong, 尚振宏 Shang; Hui, 刘辉 Liu; Jianpeng, 李健鹏 Li

doi:10.3788/lop57.021008

激光与光电子学进展

2020

DOI: 10.3788/lop57.021008

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Target Tracking Algorithm Based on Adaptive Updating of Multilayer Convolution Features

曾梦媛 Zeng Mengyuan¹,

尚振宏 Shang Zhenhong²,

刘辉 Liu Hui³

et al.

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2024

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Adaptive content-aware spatial regularized correlation filter tracking algorithm

Fasheng,

Bing,

Fuming

et al. 2024

iam

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In order to solve the annoying boundary effects in correlation filter (CF) trackers induced by cyclic shift when sampling training patches, and improve the tracking performance, an adaptive content aware spatially regularized correlation filter (ACSRCF) is proposed. Firstly, real negative samples are generated from the background area around the target object, so as to alleviate the filter degradation by the fake negative samples induced from the circularly shifted object patches. Secondly, the locality sensitive histogram (LSH) based foreground feature is extracted and incorporated with the spatial regularization weight which is updated adaptively according to the varied object-oriented appearances. Thereafter, the CF model is optimized using the alternative direction method of multipliers (ADMM) in which the model is decomposed into two sub-problems and the LSH-based features are used in iteration for obtaining the optimal solutions. Finally, the proposed method is evaluated on 5 public benchmarks. The experimental results show that the accuracy and success rate scores of our method on OTB 50 dataset are 90.3%and 66.1%, respectively, exceeding the other CF trackers .The data on the OTB100 dataset is 92.2%and 69.2%, and the accuracy first ranks among all the trackers, while the success rate is ahead of other CF trackers.

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Adaptive content-aware spatial regularized correlation filter tracking algorithm

Fasheng,

Bing,

Fuming

et al. 2024

iam

View full text Add to dashboard Cite

show abstract

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Target Tracking Algorithm Based on Adaptive Updating of Multilayer Convolution Features

Cited by 1 publication

References 0 publications

Adaptive content-aware spatial regularized correlation filter tracking algorithm

Adaptive content-aware spatial regularized correlation filter tracking algorithm

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