التفاصيل البيبلوغرافية
| العنوان: |
A Stable Multi-Object Tracking Method for Unstable and Irregular Maritime Environments. |
| المؤلفون: |
Han, Young-Suk, Jung, Jae-Yoon |
| المصدر: |
Journal of Marine Science & Engineering; Dec2024, Vol. 12 Issue 12, p2252, 14p |
| مصطلحات موضوعية: |
KALMAN filtering, AUTONOMOUS vehicles, CAMERAS, COASTS, ALGORITHMS |
| مستخلص: |
In this study, an improved stable multi-object simple online and real-time tracking (StableSORT) algorithm that was specifically designed for maritime environments was proposed to address challenges such as camera instability and irregular object motion. Specifically, StableSORT integrates a buffered IoU (B-IoU) and an observation-adaptive Kalman filter (OAKF) into the StrongSORT framework to improve tracking accuracy and robustness. A dataset was collected along the southern coast of Korea using a small autonomous surface vehicle to capture real-world maritime conditions. On this dataset, StableSORT achieved a 2.7% improvement in HOTA, 4.9% in AssA, and 2.6% in IDF1 compared to StrongSORT, and it significantly outperformed ByteTrack and OC-SORT by 84% and 69% in HOTA, respectively. These results underscore StableSORT's ability to maintain identity consistency and enhance tracking performance under challenging maritime conditions. The ablation studies further validated the contributions of the B-IoU and OAKF modules in maintaining identity consistency and tracking accuracy under challenging maritime conditions. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |