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1. Fast Fréchet Distance for Curves with Long Edges

   Gudmundsson, J.; Mirzanezhad, M.; Mohades, A.; Wenk, C. (April 2018, 3rd International Workshop on Interactive and Spatial Computing)

   Computing Fréchet distance between two curves takes roughly quadratic time. The only strongly subquadratic time algorithm has been proposed in [7] for c-packed curves. In this paper, we show that for curves with long edges the Fréchet distance computations become easier. Let P and Q be two polygonal curves in Rd with n and m vertices, respectively. We prove three main results for the case when all edges of both curves are long compared to the Fréchet distance between them: (1) a linear-time algorithm for deciding the Fréchet distance between two curves, (2) an algorithm that computes the Fréchet distance in O((n + m) log(n + m)) time, and (3) a linear-time [EQUATION]-approximation algorithm for approximating the Fréchet distance between two curves. 

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2. Fréchet Edit Distance

   Fox, Emily; Nayyeri, Amir; Perry, Jonathan James; Raichel, Benjmain (June 2024, Proceedings of the 40th International Symposium on Computational Geometry)

   In this paper we define and investigate the Fréchet edit distance problem. Here, given two polygonal curves $$\pi$$ and $$\sigma$$ and a threshhold value $$\delta$$ , we seek the minimum number of edits to $$\sigma$$ such that the Fréchet distance between the edited curve and $$\pi$$ is at most $$\delta$$. For the edit operations we consider three cases, namely, deletion of vertices, insertion of vertices, or both. For this basic problem we consider a number of variants. Specifically, we provide polynomial time algorithms for both discrete and continuous Fréchet edit distance variants, as well as hardness results for weak Fréchet edit distance variants. 

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3. Fréchet Edit Distance

   https://doi.org/10.4230/LIPIcs.SoCG.2024.58  

   Fox, Emily; Nayyeri, Amir; Perry, Jonathan James; Raichel, Benjamin (June 2024, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Mulzer, Wolfgang; Phillips, Jeff M (Ed.)

   We define and investigate the Fréchet edit distance problem. Given two polygonal curves π and σ and a non-negative threshhold value δ, we seek the minimum number of edits to σ such that the Fréchet distance between the edited σ and π is at most δ. For the edit operations we consider three cases, namely, deletion of vertices, insertion of vertices, or both. For this basic problem we consider a number of variants. Specifically, we provide polynomial time algorithms for both discrete and continuous Fréchet edit distance variants, as well as hardness results for weak Fréchet edit distance variants. 

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4. Discrete Fréchet Distance Oracles

   https://doi.org/10.4230/LIPIcs.SoCG.2024.10  

   Aronov, Boris; Farhana, Tsuri; Katz, Matthew J; Ramesh, Indu (June 2024, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Mulzer, Wolfgang; Phillips, Jeff M (Ed.)

   It is unlikely that the discrete Fréchet distance between two curves of length n can be computed in strictly subquadratic time. We thus consider the setting where one of the curves, P, is known in advance. In particular, we wish to construct data structures (distance oracles) of near-linear size that support efficient distance queries with respect to P in sublinear time. Since there is evidence that this is impossible for query curves of length Θ(n^α), for any α > 0, we focus on query curves of (small) constant length, for which we are able to devise distance oracles with the desired bounds. We extend our tools to handle subcurves of the given curve, and even arbitrary vertex-to-vertex subcurves of a given geometric tree. That is, we construct an oracle that can quickly compute the distance between a short polygonal path (the query) and a path in the preprocessed tree between two query-specified vertices. Moreover, we define a new family of geometric graphs, t-local graphs (which strictly contains the family of geometric spanners with constant stretch), for which a similar oracle exists: we can preprocess a graph G in the family, so that, given a query segment and a pair u,v of vertices in G, one can quickly compute the smallest discrete Fréchet distance between the segment and any (u,v)-path in G. The answer is exact, if t = 1, and approximate if t > 1. 

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5. The Fréchet Distance Unleashed: Approximating a Dog with a Frog

   https://doi.org/10.4230/LIPIcs.SoCG.2025.54  

   Har-Peled, Sariel; Raichel, Benjamin; Robson, Eliot W (January 2025, Schloss Dagstuhl – Leibniz-Zentrum für Informatik)

   Aichholzer, Oswin; Wang, Haitao (Ed.)

   We show that a variant of the continuous Fréchet distance between polygonal curves can be computed using essentially the same algorithm used to solve the discrete version. The new variant is not necessarily monotone, but this shortcoming can be easily handled via refinement. Combined with a Dijkstra/Prim type algorithm, this leads to a realization of the Fréchet distance (i.e., a morphing) that is locally optimal (aka locally correct), that is both easy to compute, and in practice, takes near linear time on many inputs. The new morphing has the property that the leash is always as short as possible. These matchings/morphings are more natural, and are better than the ones computed by standard algorithms - in particular, they handle noise more graciously. This should make the Fréchet distance more useful for real world applications. We implemented the new algorithm, and various strategies to obtain fast practical performance. We performed extensive experiments with our new algorithm, and released publicly available (and easily installable and usable) Julia and Python packages. In particular, the Julia implementation, for computing the regular Fréchet distance, seems to be {significantly faster} than other currently available implementations. See Table 2.2. Our algorithms can be used to compute the almost-exact Fréchet distance between polygonal curves. Implementations and numerous examples are available here: https://frechet.xyz. 

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