750 research outputs found
A Systematic Review of Algorithms with Linear-time Behaviour to Generate Delaunay and Voronoi Tessellations
Triangulations and tetrahedrizations are important geometrical discretization procedures applied to several areas, such as the reconstruction of surfaces and data visualization. Delaunay and Voronoi tessellations are discretization structures of domains with desirable geometrical properties. In this work, a systematic review of algorithms with linear-time behaviour to generate 2D/3D Delaunay and/or Voronoi tessellations is presented
Voronoi diagrams in the max-norm: algorithms, implementation, and applications
Voronoi diagrams and their numerous variants are well-established objects in computational geometry. They have proven to be extremely useful to tackle geometric problems in various domains such as VLSI CAD, Computer Graphics, Pattern Recognition, Information Retrieval, etc. In this dissertation, we study generalized Voronoi diagram of line segments as motivated by applications in VLSI Computer Aided Design. Our work has three directions: algorithms, implementation, and applications of the line-segment Voronoi diagrams. Our results are as follows: (1) Algorithms for the farthest Voronoi diagram of line segments in the Lp metric, 1 ≤ p ≤ ∞. Our main interest is the L2 (Euclidean) and the L∞ metric. We first introduce the farthest line-segment hull and its Gaussian map to characterize the regions of the farthest line-segment Voronoi diagram at infinity. We then adapt well-known techniques for the construction of a convex hull to compute the farthest line-segment hull, and therefore, the farthest segment Voronoi diagram. Our approach unifies techniques to compute farthest Voronoi diagrams for points and line segments. (2) The implementation of the L∞ Voronoi diagram of line segments in the Computational Geometry Algorithms Library (CGAL). Our software (approximately 17K lines of C++ code) is built on top of the existing CGAL package on the L2 (Euclidean) Voronoi diagram of line segments. It is accepted and integrated in the upcoming version of the library CGAL-4.7 and will be released in september 2015. We performed the implementation in the L∞ metric because we target applications in VLSI design, where shapes are predominantly rectilinear, and the L∞ segment Voronoi diagram is computationally simpler. (3) The application of our Voronoi software to tackle proximity-related problems in VLSI pattern analysis. In particular, we use the Voronoi diagram to identify critical locations in patterns of VLSI layout, which can be faulty during the printing process of a VLSI chip. We present experiments involving layout pieces that were provided by IBM Research, Zurich. Our Voronoi-based method was able to find all problematic locations in the provided layout pieces, very fast, and without any manual intervention
Analysis of the Incircle predicate for the Euclidean Voronoi diagram of axes-aligned line segments
In this paper we study the most-demanding predicate for computing the
Euclidean Voronoi diagram of axes-aligned line segments, namely the Incircle
predicate. Our contribution is two-fold: firstly, we describe, in algorithmic
terms, how to compute the Incircle predicate for axes-aligned line segments,
and secondly we compute its algebraic degree. Our primary aim is to minimize
the algebraic degree, while, at the same time, taking into account the amount
of operations needed to compute our predicate of interest.
In our predicate analysis we show that the Incircle predicate can be answered
by evaluating the signs of algebraic expressions of degree at most 6; this is
half the algebraic degree we get when we evaluate the Incircle predicate using
the current state-of-the-art approach. In the most demanding cases of our
predicate evaluation, we reduce the problem of answering the Incircle predicate
to the problem of computing the sign of the value of a linear polynomial (in
one variable), when evaluated at a known specific root of a quadratic
polynomial (again in one variable). Another important aspect of our approach is
that, from a geometric point of view, we answer the most difficult case of the
predicate via implicitly performing point locations on an appropriately defined
subdivision of the place induced by the Voronoi circle implicated in the
Incircle predicate.Comment: 17 pages, 4 figures, work presented in the paper is part of M.
Kamarianakis' M.S. thesi
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 paper introduces
the formal notion of the family of -shapes of a finite point set in
\Real^3. Each shape is a well-defined polytope, derived from the Delaunay
triangulation of the point set, with a parameter \alpha \in \Real controlling
the desired level of detail. An algorithm is presented that constructs the
entire family of shapes for a given set of size in time , worst
case. A robust implementation of the algorithm is discussed and several
applications in the area of scientific computing are mentioned.Comment: 32 page
Towards Stratification Learning through Homology Inference
A topological approach to stratification learning is developed for point
cloud data drawn from a stratified space. Given such data, our objective is to
infer which points belong to the same strata. First we define a multi-scale
notion of a stratified space, giving a stratification for each radius level. We
then use methods derived from kernel and cokernel persistent homology to
cluster the data points into different strata, and we prove a result which
guarantees the correctness of our clustering, given certain topological
conditions; some geometric intuition for these topological conditions is also
provided. Our correctness result is then given a probabilistic flavor: we give
bounds on the minimum number of sample points required to infer, with
probability, which points belong to the same strata. Finally, we give an
explicit algorithm for the clustering, prove its correctness, and apply it to
some simulated data.Comment: 48 page
09111 Abstracts Collection -- Computational Geometry
From March 8 to March 13, 2009, the Dagstuhl Seminar 09111 ``Computational Geometry \u27\u27 was held in Schloss Dagstuhl~--~Leibniz Center for Informatics.
During the seminar, several participants presented their current
research, and ongoing work and open problems were discussed. Abstracts of
the presentations given during the seminar as well as abstracts of
seminar results and ideas are put together in this paper. The first section
describes the seminar topics and goals in general.
Links to extended abstracts or full papers are provided, if available
A curvature-adapted anisotropic surface remeshing method
We present a new method for remeshing surfaces that respect the intrinsic anisotropy of the surfaces. In particular, we use the normal informations of the surfaces, and embed the surfaces into a higher dimensional space (here we use 6d). This allow us to form an isotropic mesh optimization problem in this embedded space. Starting from an initial mesh of a surface, we optimize the mesh by improving the mesh quality measured in the embedded space. The mesh is optimized by combining common local modifications operations, i.e., edge flip, edge contraction, vertex smoothing, and vertex insertion. All operations are applied directly on the 3d surface mesh. This method results a curvature-adapted mesh of the surface. This method can be easily adapted to mesh multi-patches surfaces, i.e., containing corner singularities and sharp features. We present examples of remeshed surfaces from implicit functions and CAD models
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