Translation Invariant Fr\'echet Distance Queries
Algorithmica(2021)
摘要
The Fr\'echet distance is a popular similarity measure between curves. For some applications, it is desirable to match the curves under translation before computing the Fr\'echet distance between them. This variant is called the Translation Invariant Fr\'echet distance, and algorithms to compute it are well studied. The query version, however, is much less well understood. We study Translation Invariant Fr\'echet distance queries in a restricted setting of horizontal query segments. More specifically, we prepocess a trajectory in $O(n^2 \log^2 n)$ time and space, such that for any subtrajectory and any horizontal query segment we can compute their Translation Invariant Fr\'echet distance in $O(\text{polylog} \, n)$ time. We hope this will be a step towards answering Translation Invariant Fr\'echet queries between arbitrary trajectories.
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关键词
Data structures, Trajectory data, Computational geometry, Frechet distance
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