Constructing arrangements of lines and hyperplanes with applications
SIAM Journal on Computing
An improved algorithm for constructing kth-order voronoi diagrams
IEEE Transactions on Computers
A linear-time algorithm for computing the Voronoi diagram of a convex polygon
Discrete & Computational Geometry
Applications of random sampling in computational geometry, II
Discrete & Computational Geometry - Selected papers from the fourth ACM symposium on computational geometry, Univ. of Illinois, Urbana-Champaign, June 6 8, 1988
On levels in arrangements and Voronoi diagrams
Discrete & Computational Geometry
Constructing Levels in Arrangements and Higher Order Voronoi Diagrams
SIAM Journal on Computing
Higher order Delaunay triangulations
Computational Geometry: Theory and Applications
On k-Nearest Neighbor Voronoi Diagrams in the Plane
IEEE Transactions on Computers
Critical area computation for missing material defects in VLSI circuits
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Net-Aware Critical Area Extraction for Opens in VLSI Circuits Via Higher-Order Voronoi Diagrams
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
On the complexity of higher order abstract voronoi diagrams
ICALP'13 Proceedings of the 40th international conference on Automata, Languages, and Programming - Volume Part I
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This paper revisits the k-nearest-neighbor (k-NN) Voronoi diagram and presents the first output-sensitive paradigm for its construction. It introduces the k-NN Delaunay graph, which corresponds to the graph theoretic dual of the k-NN Voronoi diagram, and uses it as a base to directly compute the k-NN Voronoi diagram in R2. In the L1, L∞ metrics this results in O((n + m) log n) time algorithm, using segment-dragging queries, where m is the structural complexity (size) of the k-NN Voronoi diagram of n point sites in the plane. The paper also gives a tighter bound on the structural complexity of the k-NN Voronoi diagram in the L∞ (equiv. L1) metric, which is shown to be O(min{k(n - k), (n - k)2}).