Real-time multi-target tracking method for ship intelligent navigation

被引：0
|
作者：
Xu H. [1 ,2 ]
Ruibo B. [2 ]
Feng H. [1 ,2 ]
机构：
[1] Key Laboratory of High Performance Ship Technology, Ministry of Education, Wuhan University of Technology, Wuhan
[2] School of Transportation, Wuhan University of Technology, Wuhan
来源：
Huazhong Keji Daxue Xuebao (Ziran Kexue Ban)/Journal of Huazhong University of Science and Technology (Natural Science Edition) | 2022年 / 50卷 / 01期
关键词：
Detector; Feature extraction; Intelligent ship; Multiple object tracking; Water surface image;
D O I：
10.13245/j.hust.220123
中图分类号：
学科分类号：
摘要：
In order to track the surrounding ship targets in real time, a ship multi-target real-time tracking method was proposed. The trained detector was used to detect all kinds of ships encountered during navigation, and then the detection results were correlated and matched by the improved deep sort tracking algorithm, so as to complete the real-time tracking of multiple ship targets. The feature extraction network in deeport algorithm was trained by generating ship re identification data set, and the update mode of feature vector set in apparent matching is improved, so that the set with limited space could store more kinds of apparent features. The experimental results show that the proposed algorithm can significantly improve the tracking performance, in which the number of track switching identity is reduced by 11%, and the number of track interruptions is reduced by 5.8%. It can meet the accuracy and real-time requirements of marine ship target perception. © 2022, Editorial Board of Journal of Huazhong University of Science and Technology. All right reserved.
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页码：138 / 143
页数：5
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