Research on underwater target tracking method based on SIFT and KCF algorithm

Zhijian Gu; Ying Wang; Yipen Wu; Zhikai Huang; Jianfeng Xie; Qinfeng Xi

doi:10.1117/12.2636616

8 May 2022 Research on underwater target tracking method based on SIFT and KCF algorithm

Zhijian Gu, Ying Wang, Yipen Wu, Zhikai Huang, Jianfeng Xie, Qinfeng Xi

Proceedings Volume 12249, 2nd International Conference on Internet of Things and Smart City (IoTSC 2022）; 1224918 (2022) https://doi.org/10.1117/12.2636616
Event: 2022 2nd International Conference on Internet of Things and Smart City (IoTSC 2022）, 2022, Xiamen, China

Abstract

In the process of water quality monitoring, qualitative evaluation can be carried out according to the changes in the number of underwater animals and the state of motion and other parameters, because of the underwater image resolution is low, mistracking and loss can occur when tracking underwater targets, this paper proposes a matching algorithm based on scale invariant feature transform (SIFT) and nuclear correlation filter (KCF) of underwater target tracking algorithm. SIFT algorithm was used for feature extraction to obtain the detection frame, and the improved HOG feature was used for KCF training and tracking. According to the experimental results, it can effectively detect and track underwater fish under complicated underwater conditions.

Citation Download Citation

Zhijian Gu, Ying Wang, Yipen Wu, Zhikai Huang, Jianfeng Xie, and Qinfeng Xi "Research on underwater target tracking method based on SIFT and KCF algorithm", Proc. SPIE 12249, 2nd International Conference on Internet of Things and Smart City (IoTSC 2022）, 1224918 (8 May 2022); https://doi.org/10.1117/12.2636616

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