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Ship behavior recognition based on infrared video analysis in a maritime environment

机译：基于海洋环境红外视频分析的船舶行为识别

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In order to improve the monitoring capability of officer on watch for the environment around the own ship, cover the shortage of RADAR and AIS in ship behavior recognition field, this paper proposes a ship behavior recognition algorithm based on video analysis. After analyzing the ship behavior we found that the silhouette's size and shape variation of ship in infrared image were related to its behavior over a period of time, that is to say when the distance between the own ship and the target ship has decreased during this period, its silhouette's size would increase. And when the target ship is heading toward the own ship directly and the distance between them has decreased (the DCPA (Distance to Closest Point of Approach) is very small, and the TCPA (Time to Closest Point of Approach) is decreasing), the silhouette's size of the target ship would enlarge, nevertheless, its silhouette's shape would have no significant changes. According to these characteristics of ship behavior, the height of target ship's silhouette is used to represent silhouette's size and the ratio between the width and the height of the target ship's silhouette is used to represent silhouette's shape in the ship behavior recognition algorithm we proposed. And then the least square method is used to fit the height and the ratio into straight line during this period respectively, whose slope reflects the changing trend and variation of target ship's silhouette. At last, the recognition algorithm was verified by analyzing infrared video in a maritime environment, which shows that the characteristic of ship behavior summarized by this paper is correct and the recognition algorithm based on them is feasible.
机译：为了改善手表官员的监测能力，为自己船舶周围的环境，涵盖雷达和AIS在船舶行为识别领域的短缺，本文提出了一种基于视频分析的船舶行为识别算法。在分析船舶行为后，我们发现红外图像中船舶的尺寸和形状变化与其行为在一段时间内与其行为有关，也就是说，当在此期间，当自己的船舶和目标船之间的距离下降时，其轮廓的尺寸将增加。当目标船直接向自己的船朝向自己的船舶时，它们之间的距离减少（DCPA（到最近的接近点）非常小，而TCPA（最近接近的时间）是降低的），剪影的目标船的大小将扩大，但其轮廓的形状没有重大变化。根据船舶行为的这些特征，使用目标船舶轮廓的高度来表示轮廓的尺寸，并且目标船舶轮廓的宽度与高度之间的比率用于表示我们提出的船舶行为识别算法中的轮廓的形状。然后，在此期间，使用最小二乘法将高度和比例拟合到直线中，其斜率反映了目标船舶轮廓的变化趋势和变化。最后，通过分析海洋环境中的红外视频来验证识别算法，这表明本文总结了船舶行为的特性是正确的，并且基于它们的识别算法是可行的。

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