41540520
Space Searching for Intersecting Objects
Determining or counting geometric objects that intersect another geometric query object is at the core of algorithmic problems in a number of applied areas of computer science. This article presents a family of space-efficient data structures that realize sublinear query time for points, line segments, lines and polygons in the plane, and points, line segments, plaraes, and polyhedra in three dimensions.
12582971
Stabbing line segments
An algorithm for the geometric problem of determining a line (called a stabbing line) which intersects each ofn given line segments in the plane is presented. As a matter of fact, the algorithm computes a description of all stabbing lines. A purely geometric fact is proved which infers that this description requiresO(n) space to be specified. Our algorithm computes it inO(n logn) time which is optimal in the worst case.Using the description of the stabbing lines, we are able to decide inO(logn) time whether or not a specified line is a stabbing line. Finally, the problem of maintaining the description of all stabbing lines while inserting and deleting line segments is addressed.
33731652
Rectangular Point Location in d Dimensions with Applications
31366541
An optimal algorithm for constructing the weighted voronoi diagram in the plane
Let S denote a set of n points in the plane such that each point p has assigned a positive weight w(p) which expresses its capability to influence its neighbourhood. In this sense, the weighted distance of an arbitrary point x from p is given by de(x,p)/w(p) where de denotes the Euclidean distance function. The weighted Voronoi diagram for S is a subdivision of the plane such that each point p in S is associated with a region consisting of all points x in the plane for which p is a weighted nearest point of S. 
 
An algorithm which constructs the weighted Voronoi diagram for S in O(n2) time is outlined in this paper. The method is optimal as the diagram can consist of Θ(n2) faces, edges and vertices.
2265636
Polygonal Intersection Searching
17674541
Some methods of computational geometry applied to computer graphics
Abstract Windowing a two-dimensional picture means to determine those line segments of the picture that are visible through an axis-parallel window. A study of some algorithmic problems involved in windowing a picture is offered. Some methods from computational geometry are exploited to store the picture in a computer such that (1) those line segments inside or partially inside of a window can be determined efficiently, and (2) the set of those line segments can be maintained efficiently while the window is moved parallel to a coordinate axis and/or it is enlarged or reduced.
46726120
The union of balls and its dual shape
Efficient algorithms are described for computing topological, combinatorial, and metric properties of the union of finitely many spherical balls in ℝd. These algorithms are based on a simplicial complex dual to a decomposition of the union of balls using Voronoi cells, and on short inclusion-exclusion formulas derived from this complex. The algorithms are most relevant in ℝ3 where unions of finitely many balls are commonly used as models of molecules.
12111408
Cutting dense point sets in half
A <italic>halving hyperplane</italic> of a set <italic>S</italic> of <italic>n</italic> points in <bold>R</bold><supscrpt><italic>d</italic></supscrpt> contains <italic>d</italic> affinely independent points of <italic>S</italic> so that equally many of the points off the hyperplane lie in each of the two half-spaces. We prove bounds on the number of halving hyperplanes under the condition that the ratio of largest over smallest distance between any two points is at most δ<italic>n</italic><supscrpt>1/<italic>d</italic></supscrpt>, δ some constant. Such a set <italic>S</italic> is called <italic>dense</italic>.
In <italic>d</italic>=2 dimensions, the number of halving lines for a dense set can be as much as &OHgr;(<italic>n</italic>log<italic>n</italic>), and it cannot exceed <italic>O</italic>(<italic>n</italic><supscrpt>5/4</supscrpt>/log*<italic>n</italic>). The upper bound improves over the current best bound of <italic>O</italic>(<italic>n</italic><supscrpt>3/2</supscrpt>/log*<italic>n</italic>) which holds more generally without any density assumption. In <italic>d</italic>=3 dimensions we show that <italic>O</italic>(<italic>n</italic><supscrpt>7/3</supscrpt>) is an upper bound on the number of halving planes for a dense set. The proof is based on a metric argument that can be extended to <italic>d</italic>≥4 dimensions, where it leads to <italic>O</italic>(<italic>n</italic><supscrpt><italic>d</italic>−2/<italic>d</italic></supscrpt>) as an upper bound for the number of halving hyperplanes.
6301471
Adaptive Simplicial Grids from Cross-Sections of Monotone Complexes
We study the maintenance of a simplicial grid or complex under changing density requirements. The proposed method works in any fixed dimension and generates grids by projecting cross-sections of a monotone simplicial complex that lives in one dimension higher than the grid. The density of the grid is adapted by locally moving the cross-section up or down along the extra dimension.
53237055
Three-dimensional alpha shapes
Frequently, data in scientific computing is in its abstract form a finite point set in space, and it is sometimes useful or required to compute what one might call the “shape” of the set. For that purpose, this article introduces the formal notion of the family of α-shapes of a finite point set in R 3 . Each shape is a well-defined polytope, derived from the Delaunay triangulation of the point set, with a parameter α e R controlling the desired level of detail. An algorithm is presented that constructs the entire family of shapes for a given set of size n in time 0(n 2 ) , worst case. A robust implementation of the algorithm is discussed, and several applications in the area of scientific computing are mentioned.
7437367
Vines and vineyards by updating persistence in linear time
Persistent homology is the mathematical core of recent work on shape, including reconstruction, recognition, and matching. Its pertinent information is encapsulated by a pairing of the critical values of a function, visualized by points forming a diagram in the plane. The original algorithm in [10] computes the pairs from an ordering of the simplices in a triangulation and takes worst-case time cubic in the number of simplices. The main result of this paper is an algorithm that maintains the pairing in worst-case linear time per transposition in the ordering. A side-effect of the algorithm's analysis is an elementary proof of the stability of persistence diagrams [7] in the special case of piecewise-linear functions. We use the algorithm to compute 1-parameter families of diagrams which we apply to the study of protein folding trajectories.