[1]DAI Yutong,CHEN Zhiguo,FU Yi.Anti-occlusion retracking technology for a moving target based on correlation filtering[J].CAAI Transactions on Intelligent Systems,2021,16(4):630-640.[doi:10.11992/tis.202005027]
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Anti-occlusion retracking technology for a moving target based on correlation filtering

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 16 Number of periods: 2021 4 Page number: 630-640 Column: 学术论文—机器学习 Public date: 2021-07-05
Title:
Anti-occlusion retracking technology for a moving target based on correlation filtering
Author(s):
DAI Yutong1;  CHEN Zhiguo1;  FU Yi2
1. School of Artificial Intelligence and Computer, Jiangnan University, Wuxi 214122, China;
2. Wuxi Research Center of Environmental Science and Engineering, Wuxi 214153, China
Keywords:
object tracking; correlation filter; multi-feature fusion; ULBP; Gaussian mask; peak-to-average ratio; Kalman prediction; anti-occlusion
CLC:
TP391.41
DOI:
10.11992/tis.202005027
Abstract:
To address the poor anti-occlusion effect of correlation filtering, this paper proposes an anti-occlusion correlation filtering algorithm by means of multifeature fusion based on efficient convolution operators handcraft. First, based on the framework of correlation filtering, a method of linearly weighted fusion is adopted to deal with the target uniform local binary pattern texture feature and the target histogram of oriented gradients feature. Second, the Gaussian mask function is used during the model establishment and update phase to ease the boundary effect caused by cyclic shift. Lastly, the target state is judged by calculating the peak-to-average ratio of the target maximum response value, and the Kalman algorithm is utilized as the relocation strategy after the target is blocked. Experimental results show that the average accuracy of the proposed algorithm reaches 87.3%, and the success rate reaches 76.5% on 16 test sequences, which are 27.7% and 23.7% higher than those of the baseline algorithm, respectively.
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