An Anti-occlusion Ship Tracking Method based on YOLOX and Improved Matching Algorithm

In inland waterways, vision-based maritime vessel tracking technology is crucial for maritime safety. Due to varying vessel speeds and angles, tracking vessels in complex environments poses a significant challenge. Currently, the mainstream video tracking method is the “Tracking-by-detection” (TBD) approach, which can meet basic tracking requirements. However, its reliance on shape-based recognition leads to bulky models and challenges in improving accuracy. To address vessel tracking confusion in complex scenarios, we introduced ship motion direction parameters into the Hungarian matching algorithm. Specifically, by combining IOU with ship motion direction, we achieved an efficient tracking mechanism that reduces computational costs. Additionally, by integrating YOLOX with the matching module, we improved tracking efficiency. Our proposed method demonstrates excellent performance on an inland waterway video dataset, showing significant improvements in MOTA compared to other methods, along with a noticeable reduction in ship ID switches.