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首页> 外文会议>ICA3PP 2014 >Vessel Motion Pattern Recognition Based on One-Way Distance and Spectral Clustering Algorithm
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Vessel Motion Pattern Recognition Based on One-Way Distance and Spectral Clustering Algorithm

机译：基于单向距离和光谱聚类算法的血管运动模式识别

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摘要

Identification of vessel motion pattern from large amount of maritime data can help to high level contextual information and improve the effectiveness of surveillance technologies. Vessel routes belonged to certain motion pattern can provide useful information on daily patterns and transit duration. Therefore an approach to identify motion pattern is presented. In paper, the distance similarity matrix of the trajectory dataset was constructed by using the measurement method in trajectory with one-way distance. The regular motion patterns of vessels were extracted from the trajectories spatial distribution learnt by the spectral clustering algorithm. Finally motion patterns of vessel traveling in Qiongzhou strait was extracted using the proposed method. The results showed that the method has high precision on clustering the vessel trajectories and is applicable to identify movement patterns of vessels in maritime areas such as coastal ports, narrow waterway and traffic complex area.
机译：从大量海上数据的识别血管运动模式可以帮助高级语境信息，提高监控技术的有效性。属于某些运动模式的船舶路线可以提供有关日常模式和运输持续时间的有用信息。因此，提出了一种识别运动模式的方法。在纸质中，通过在单向距离中使用轨迹中的测量方法来构造轨迹数据集的距离相似度矩阵。从光谱聚类算法学习的轨迹空间分布中提取血管的规则运动模式。最后用所提出的方法提取琼州海峡中行驶血管行驶的运动模式。结果表明，该方法在聚类血管轨迹上具有高精度，适用于识别海上港口，狭窄水路和交通综合区等海上地区船舶的运动模式。

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