We develop algorithms to compute edge sequences, Voronoi diagrams, shortest path maps, the Fréchet distance, and the diameter for a polyhedral surface. Distances on the surface are measured either by the length of a Euclidean shortest path or by link distance.Key words: Polyhedral Surface, Voronoi Diagram, Shortest Path Map, Fréchet distance, Diameter, Link Distance, Euclidean Shortest Path
IntroductionTwo questions are invariably encountered when dealing with shortest path problems. The first question is how to represent the combinatorial structure of a shortest path. In the plane with polygonal obstacles, a shortest path can only turn at obstacle vertices, so a shortest path can be combinatorially described as a sequence of obstacle vertices [28]. On a polyhedral surface, a shortest path need not turn at vertices [35], so a path is often described combinatorially by an edge sequence that represents the sequence of edges encountered by the path [1]. A benefit of representing shortest paths by edge sequences is that a series of unfolding rotations can be used to reduce the problem of computing a shortest path on a polyhedral surface into a two-dimensional problem. This process is described more fully in section 3.The second commonly encountered shortest path question is how to compute shortest paths in a problem space with M vertices. The following preprocessing schemes compute combinatorial representations of all possible shortest paths. In a $ This work has been supported by the National Science Foundation grant NSF CAREER CCF-0643597.$$ A previous version of this work has been presented in [21]. February 21, 2009 simple polygon, Guibas et al. [28] give an optimal Θ(M ) preprocessing scheme that permits a shortest path to be computed between any two points in O(log M ) time. In the plane with polygonal obstacles, Chiang and Mitchell [16] support shortest path queries between any two points after O(M 11 ) preprocessing. On a convex polyhedral surface, Mount [37] shows that Θ(M 4 ) combinatorially distinct shortest path edge sequences exist, and Schevon and O'Rourke [40] show that only Θ(M 3 ) of these edge sequences are maximal (i.e., they cannot be extended at either end without creating a suboptimal path). Agarwal et al.
Preprint submitted to Elsevier[1] use these properties to compute the Θ(M 4 ) shortest path edge sequences in O(M 6 2 α(M ) log M ) time and the diameter in O(M 8 log M ) time, where α(M ) is the inverse Ackermann function. The diameter is the largest shortest path distance between any two points on the surface. Despite recent efforts by Chandru et al. [13] to improve the runtimes of Agarwal et al.[1], these runtimes have not improved since 1997. Our main result improves the edge sequence and diameter algorithms of [1] by a linear factor. We achieve this improvement by combining the star unfolding technique of [1] with the kinetic Voronoi diagram structure of Albers et al. [3]. A kinetic Voronoi diagram allows its defining point sites to move. A popular alternative to precomputing...