A Robust Trajectory Similarity Measure Method for Classical Trajectory
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摘要:
针对经典轨迹与实时轨迹之间的大差异性，该文利用最长公共子序列理论，提出一种鲁棒的轨迹相似度量方法。该方法首先利用点到线段之间的距离判断经典轨迹的点与实时轨迹的线段是否一致；然后利用改进的多对1最长公共子序列算法，计算经典轨迹与实时轨迹之间的最长公共子序列长度；最后将最长公共子序列长度与经典轨迹的点数的比值作为经典轨迹与实时轨迹之间的相似度。实验说明该算法的鲁棒性，该算法能够有效解决经典轨迹与实时轨迹之间的大差异轨迹相似度量问题。
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关键词:
- 轨迹相似度量 /
- 大差异轨迹 /
- 多对1最长公共子序列 /
- 鲁棒计算 /
- 经典轨迹
Abstract:In view of the great difference between classical trajectory and real-time trajectory, a robust trajectory similarity measurement method is proposed based on the longest common subsequence theory. Firstly, the distance between point and line segment is used to judge whether the point of classical trajectory is consistent with the line segment of real-time trajectory. Secondly, the longest common subsequence length between classical trajectory and real-time trajectory is calculated by using the improved multi-to-one longest common subsequence algorithm. Finally, the ratio of the longest common subsequence length to the number of points of the classical trajectory is taken as the similarity between the classical trajectory and the real-time trajectory. Experiments show that the algorithm is robust and can effectively solve the problem of similarity measurement between the classical trajectories and real-time trajectories.
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