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Finding long and similar parts of trajectories

机译:寻找轨迹的长且相似的部分

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摘要

A natural time-dependent similarity measure for two trajectories is their average distance at corresponding times. We give algorithms for computing the most similar subtrajectories under this measure, assuming the two trajectories are given as two polygonal, possibly self-intersecting lines with time stamps. For the case when a minimum duration of the subtrajectories is specified and the subtrajectories must start at corresponding times, we give a linear-time algorithm. The algorithm is based on a result of independent interest: We present a linear-time algorithm to find, for a piece-wise monotone function, an interval of at least a given length that has minimum average value. In the case that the subtrajectories may start at non-corresponding times, it appears difficult to give exact algorithms, even if the duration of the subtrajectories is fixed. For this case, we give (1+ε)-approximation algorithms, for both fixed duration and when only a minimum duration is specified.
机译:两个轨迹的自然时间相关性相似性度量是它们在相应时间的平均距离。我们给出了在此度量下计算最相似子轨迹的算法,假设两条轨迹给出为两条带时间戳的多边形,可能自相交的线。对于指定了子轨迹的最小持续时间并且子轨迹必须在相应时间开始的情况,我们给出了线性时间算法。该算法基于独立兴趣的结果:我们提出了一种线性时间算法,以查找分段单调函数的至少给定长度的间隔,该间隔的平均值最小。在子轨迹可能在不对应的时间开始的情况下,即使子轨迹的持续时间是固定的,也很难给出精确的算法。对于这种情况,对于固定持续时间和仅指定最小持续时间的情况,我们给出(1 +ε)近似算法。

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