An O(n^{5/2} log n) Algorithm for the Rectilinear Minimum Link-Distance Problem in Three Dimensions (Extended Abstract)

In this paper we consider the Rectilinear Minimum Link-Distance Problem in Three Dimensions. The problem is well studied in two dimensions, but is relatively unexplored in higher dimensions. We solve the problem in O(B n log n) time, where n is the number of corners among all obstacles, and B is the size of a BSP decomposition of the space containing the obstacles. It has been shown that in the worst case B = Theta(n^{3/2}), giving us an overall worst case time of O(n^{5/2} log n). Previously known algorithms have had worst-case running times of Omega(n^3)

Grid Vertex-Unfolding Orthogonal Polyhedra

An edge-unfolding of a polyhedron is produced by cutting along edges and flattening the faces to a *net*, a connected planar piece with no overlaps. A *grid unfolding* allows additional cuts along grid edges induced by coordinate planes passing through every vertex. A vertex-unfolding permits faces in the net to be connected at single vertices, not necessarily along edges. We show that any orthogonal polyhedron of genus zero has a grid vertex-unfolding. (There are orthogonal polyhedra that cannot be vertex-unfolded, so some type of "gridding" of the faces is necessary.) For any orthogonal polyhedron P with n vertices, we describe an algorithm that vertex-unfolds P in O(n^2) time. Enroute to explaining this algorithm, we present a simpler vertex-unfolding algorithm that requires a 3 x 1 refinement of the vertex grid.Comment: Original: 12 pages, 8 figures, 11 references. Revised: 22 pages, 16 figures, 12 references. New version is a substantial revision superceding the preliminary extended abstract that appeared in Lecture Notes in Computer Science, Volume 3884, Springer, Berlin/Heidelberg, Feb. 2006, pp. 264-27

Constructing Binary Space Partitions for Orthogonal Rectangles in Practice

The original publication is available at www.springerlink.comIn this paper, we develop a simple technique for constructing a I3inary Space Partition (nSP) for a set of orthogonal rectangles in IR3. OUf algorithm has the novel feature that it tunes its performance to the geometric properties of the rectangles, e.g., their aspect ratios. "Fe have implemented our algorithm and tested its performance on real data scti). V\.Tc have also systematically compared the performance of our algorithm with that of other techniques presented in the literature. Our studies show that our algorithm constructs nsps of near-linear size and small height in practice, has fast running times, and answers queries efficiently. It is a method of choice for constructing BSPs for orthogonal rectangles

Binary Space Partitions for Fat Rectangles

This is the published version. Copyright © 2000 Society for Industrial and Applied Mathematic

Optimal binary space partitions for orthogonal objects

A binary space partition, or BSP is a scheme for recursively dividing a configuration of objects by hyperplanes until all objects are separated. BSPs are widely used in computer graphics as the underlying data structure for computations such as real-time hidden-surface removal, ray tracing, and solid modelling. In these applications, the computational cost is directly related to the size of the BSP, ie the toal number of fragments of the objects generated by the partition. Until recently, the question of minimizing the size of BSPs for given inputs had been studied only empirically. We concentrate here on ortogonal objects, a case which arises frequently in practice and deserves special attention. We construct BSPs of linear size for any set of orthogonal line segments in the plane. In three dimensions, BSPs of size O(n1.5) for any set of n mutually orthogonal line segments or rectangles are constructed. These bounds are optimal and may be contrasted with the omega(n2) bound for general polygonal objects in R3

Approximately Optimum Search Trees in External Memory Models

We examine optimal and near optimal solutions to the classic binary search tree problem of Knuth. We are given a set of n keys (originally known as words), B_1, B_2, ..., B_n and 2n+1 frequencies. {p_1, p_2, ..., p_n} represent the probabilities of searching for each given key, and {q_0, q_1, ..., q_n} represent the probabilities of searching in the gaps between and outside of these keys. We have that Σ_{i=0}^n q_i + Σ_{i=1}^n p_i = 1. We also assume without loss of generality that q_{i-1}+p_i+q_i != 0 for any i ϵ {1,...,n}. The keys must make up the internal nodes of the tree while the gaps make up the leaves. Our goal is to construct a binary search tree such that expected cost of search is minimized. First, we re-examine an approximate solution of Guttler, Mehlhorn and Schneider which was shown to have a worst case bound of c * H + 2 where c >= 1/(H(1/3,2/3)) ~ 1.08, and H = Σ_{i=1}^{n} p_i * log_2(1/p_i) + Σ_{j=0}^{n} q_i * log_2(1/q_j) is the entropy of the distribution. We give an improved worst case bound on the heuristic of H+4. Next, we examine the optimum binary search tree problem under a model of external memory. We use the Hierarchical Memory Model of Aggarwal et al. The model has an unlimited number of registers, R_1, R_2, ... each with its own location in memory (a positive integer). We have a set of memory sizes m_1, m_2, ..., m_l which are monotonically increasing. Each memory level has a finite size except m_l which we assume has infinite size. Each memory level has an associated cost of access c_1, c_2, ..., c_l. We assume that c_1 < c_2 < ... < c_l. We propose two approximate solutions which run in O(n) time where n is the number of words in our data set. Using these methods, we improve upon a bound given in Thite's 2001 thesis under the related HMM_2 model in the approximate setting. We also examine the related problem of binary trees on multisets of probabilities where keys are unordered and we do not differentiate between which probabilities must be leaves, and which must be internal nodes. We provide a simple O(n log_2(n)) algorithm that is within an additive (n+1)(2n) of optimal on a multiset of n keys

The three-dimensional art gallery problem and its solutions

This thesis addressed the three-dimensional Art Gallery Problem (3D-AGP), a version of the art gallery problem, which aims to determine the number of guards required to cover the interior of a pseudo-polyhedron as well as the placement of these guards. This study exclusively focused on the version of the 3D-AGP in which the art gallery is modelled by an orthogonal pseudo-polyhedron, instead of a pseudo-polyhedron. An orthogonal pseudopolyhedron provides a simple yet effective model for an art gallery because of the fact that most real-life buildings and art galleries are largely orthogonal in shape. Thus far, the existing solutions to the 3D-AGP employ mobile guards, in which each mobile guard is allowed to roam over an entire interior face or edge of a simple orthogonal polyhedron. In many realword applications including the monitoring an art gallery, mobile guards are not always adequate. For instance, surveillance cameras are usually installed at fixed locations. The guard placement method proposed in this thesis addresses such limitations. It uses fixedpoint guards inside an orthogonal pseudo-polyhedron. This formulation of the art gallery problem is closer to that of the classical art gallery problem. The use of fixed-point guards also makes our method applicable to wider application areas. Furthermore, unlike the existing solutions which are only applicable to simple orthogonal polyhedra, our solution applies to orthogonal pseudo-polyhedra, which is a super-class of simple orthogonal polyhedron. In this thesis, a general solution to the guard placement problem for 3D-AGP on any orthogonal pseudo-polyhedron has been presented. This method is the first solution known so far to fixed-point guard placement for orthogonal pseudo-polyhedron. Furthermore, it has been shown that the upper bound for the number of fixed-point guards required for covering any orthogonal polyhedron having n vertices is (n3/2), which is the lowest upper bound known so far for the number of fixed-point guards for any orthogonal polyhedron. This thesis also provides a new way to characterise the type of a vertex in any orthogonal pseudo-polyhedron and has conjectured a quantitative relationship between the numbers of vertices with different vertex configurations in any orthogonal pseudo-polyhedron. This conjecture, if proved to be true, will be useful for gaining insight into the structure of any orthogonal pseudo-polyhedron involved in many 3-dimensional computational geometrical problems. Finally the thesis has also described a new method for splitting orthogonal polygon iv using a polyline and a new method for splitting an orthogonal polyhedron using a polyplane. These algorithms are useful in applications such as metal fabrication

On Constant Factors in Comparison-Based Geometric Algorithms and Data Structures

Many standard problems in computational geometry have been solved asymptotically optimally as far as comparison-based algorithms are concerned, but there has been little work focusing on improving the constant factors hidden in big-Oh bounds on the number of comparisons needed. In this thesis, we consider orthogonal-type problems and present a number of results that achieve optimality in the constant factors of the leading terms, including: - An output-sensitive algorithm that computes the maxima for a set of n points in two dimensions using 1n log(h) + O(n sqrt(log(h))) comparisons, where h is the size of the output. - A randomized algorithm that computes the maxima in three dimensions that uses 1n log(n) + O(n sqrt(log(n))) expected number of comparisons. - A randomized output-sensitive algorithm that computes the maxima in three dimensions that uses 1n log(h) + O(n log^(2/3)(h)) expected number of comparisons, where h is the size of the output. - An output-sensitive algorithm that computes the convex hull for a set of n points in two dimensions using 1n log(h) + O(n sqrt(log(h))) comparisons and O(n sqrt(log(h))) sidedness tests, where h is the size of the output. - A randomized algorithm for detecting whether of a set of n horizontal and vertical line segments in the plane intersect that uses 1n log(n) +O(n sqrt(log(n))) expected number of comparisons. - A data structure for point location among n axis-aligned disjoint boxes in three dimensions that answers queries using at most (3/2)log(n)+ O(log(log(n))) comparisons. The data structure can be extended to higher dimensions and uses at most (d/2)log(n)+ O(log(log(n))) comparisons. - A data structure for point location among n axis-aligned disjoint boxes that form a space-filling subdivision in three dimensions that answers queries using at most (4/3)log(n)+ O(sqrt(log(n))) comparisons. The data structure can be extended to higher dimensions and uses at most ((d+1)/3)log(n)+ O(sqrt(log(n))) comparisons. Our algorithms and data structures use a variety of techniques, including Seidel and Adamy's planar point location method, weighted binary search, and height-optimal BSP trees