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Exact algorithms for partial curve matching via the Fréchet distance
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Source Symposium on Discrete Algorithms archive
Proceedings of the Nineteenth Annual ACM -SIAM Symposium on Discrete Algorithms table of contents
New York, New York
Pages 645-654  
Year of Publication: 2009
Authors
Kevin Buchin  Utrecht Univ., Netherlands
Maike Buchin  Utrecht Univ., Netherlands
Yusu Wang  The Ohio State Univ, Columbus, OH
Publisher
Society for Industrial and Applied Mathematics  Philadelphia, PA, USA
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ABSTRACT

Curve matching is a fundamental problem that occurs in many applications. In this paper, we study the problem of measuring partial similarity between curves. Specifically, given two curves, we wish to maximize the total length of subcurves that are close to each other, where closeness is measured by the Fréchet distance, a common distance measure for curves. The resulting maximal length is called the partial Fréchet similarity between the two input curves.

Given two polygonal curves P and Q in Rd of size m and n, respectively, we present the first exact algorithm that runs in polynomial time to compute fδ(P, Q), the partial Fréchet similarity between P and Q, under the L1 and L norms. Specifically, we formulate the problem of computing fδ(P, Q) as a longest path problem, and solve it in O(mn(m + n) log(mn)) time, under the L1 or L norm, using a "shortest-path map" type decomposition. To the best of our knowledge, this is the first paper to study this natural definition of partial curve similarity in the continuous setting (with all points in the curve considered), and present a polynomial-time exact algorithm for it.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Kevin Buchin: colleagues
Maike Buchin: colleagues
Yusu Wang: colleagues