Let P be a simple polygon with n vertices. For any two points in P, the geodesic distance between them is the length of the shortest path that connects them among all paths contained in P. Given a set S of m sites being a subset of the vertices of P, we present the first randomized algorithm to compute the geodesic farthest-point Voronoi diagram of S in P running in expected O(n + m) time. That is, a partition of P into cells, at most one cell per site, such that every point in a cell has the same farthest site with respect to the geodesic distance. This algorithm can be extended to run in expected O(n + m log m) time when S is an arbitrary set of m sites contained in P.
@InProceedings{barba:LIPIcs.SoCG.2019.12, author = {Barba, Luis}, title = {{Optimal Algorithm for Geodesic Farthest-Point Voronoi Diagrams}}, booktitle = {35th International Symposium on Computational Geometry (SoCG 2019)}, pages = {12:1--12:14}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-95977-104-7}, ISSN = {1868-8969}, year = {2019}, volume = {129}, editor = {Barequet, Gill and Wang, Yusu}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2019.12}, URN = {urn:nbn:de:0030-drops-104161}, doi = {10.4230/LIPIcs.SoCG.2019.12}, annote = {Keywords: Geodesic distance, simple polygons, farthest-point Voronoi diagram} }
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