Efficient Maritime Traffic Flow Analysis Using YOLOv8 and DeepSORT for Vessel Detection and Tracking

This study presents a novel method for vessel traffic flow analysis based on video image recognition, utilizing the YOLOv8 object detection algorithm and the DeepSORT multi-object tracking technique. By integrating these advanced technologies, the proposed method achieves efficient and accurate detection and continuous tracking of vessels, enabling effective statistical analysis of vessel traffic flow and motion trajectories. The process begins with the YOLOv8 algorithm, which identifies vessel targets in video frames. Subsequently, the DeepSORT algorithm is employed to track the detected vessels continuously. Finally, statistical analysis of the tracked vessels provides critical information, such as vessel traffic flow and motion trajectories. This information is valuable for applications in vessel traffic management, safety monitoring, and related fields. The proposed method offer a robust solution for vessel traffic flow analysis.

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Publication Details

Published
2025-08-08
DOI
https://doi.org/10.1109/iaeac65194.2025.11166335
Primary Topic
Maritime Navigation and Safety
Type
article
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article

Efficient Maritime Traffic Flow Analysis Using YOLOv8 and DeepSORT for Vessel Detection and Tracking

Xiaofeng Zou, Xiang Zhong, Xinglong Liu, Yongtao Wang et al.
Maritime Navigation and Safety
article

Efficient Maritime Traffic Flow Analysis Using YOLOv8 and DeepSORT for Vessel Detection and Tracking

Xiaofeng Zou, Xiang Zhong, Xinglong Liu, Yongtao Wang, W.-Y. Wang
article en

Abstract

This study presents a novel method for vessel traffic flow analysis based on video image recognition, utilizing the YOLOv8 object detection algorithm and the DeepSORT multi-object tracking technique. By integrating these advanced technologies, the proposed method achieves efficient and accurate detection and continuous tracking of vessels, enabling effective statistical analysis of vessel traffic flow and motion trajectories. The process begins with the YOLOv8 algorithm, which identifies vessel targets in video frames. Subsequently, the DeepSORT algorithm is employed to track the detected vessels continuously. Finally, statistical analysis of the tracked vessels provides critical information, such as vessel traffic flow and motion trajectories. This information is valuable for applications in vessel traffic management, safety monitoring, and related fields. The proposed method offer a robust solution for vessel traffic flow analysis.

Minjiang University (CN), Institute of Navigation (US)
Openalex Percentile: Top 68%
Maritime Navigation and Safety
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Efficient Maritime Traffic Flow Analysis Using YOLOv8 and DeepSORT for Vessel Detection and Tracking — Xiaofeng Zou, Xiang Zhong, et al. · (2025) | TGRS Research Map | TGRS