船舶多目标跟踪的VTS传感器信息融合结构

Jingxue Chen, Jie Wang, Huajie Lu
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引用次数: 0

摘要

利用AIS、雷达和摄像机的VTS传感器进行信息融合对水上交通监控具有重要意义。首先,结合基于深度学习的检测器生成的边界框,将岸基闭路电视摄像机引入到船舶目标的检测和定位中。此外,本文还比较了模拟水上交通场景中中心级和轨道级的信息融合结构。最后,本文介绍了一种针对虚警率较大的传感器的航迹选择方法,在充分考虑各种VTS传感器的优缺点的情况下,获得两种融合结构上性能更好的航迹。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Information fusion structure of VTS sensors for multi-target tracking of vessels
Information fusion using VTS sensors of AIS, radar and camera are of great significance to the waterborne traffic supervision. Firstly, this paper invites shore-based CCTV cameras into detection and location of vessel targets combining with bounding boxes generated by deep-learning based detectors. Besides, this paper compares information fusion structure of central-level and track-level in simulated waterborne traffic scenario. Finally, this paper introduces a track selection method for sensors with large false alarm rate to obtain tracks with better performance on both fusion structure when fully considering strengths and weaknesses of all kinds of VTS sensors.
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