2,625 research outputs found

    Gap Processing for Adaptive Maximal Poisson-Disk Sampling

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    In this paper, we study the generation of maximal Poisson-disk sets with varying radii. First, we present a geometric analysis of gaps in such disk sets. This analysis is the basis for maximal and adaptive sampling in Euclidean space and on manifolds. Second, we propose efficient algorithms and data structures to detect gaps and update gaps when disks are inserted, deleted, moved, or have their radius changed. We build on the concepts of the regular triangulation and the power diagram. Third, we will show how our analysis can make a contribution to the state-of-the-art in surface remeshing.Comment: 16 pages. ACM Transactions on Graphics, 201

    The Topology ToolKit

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    This system paper presents the Topology ToolKit (TTK), a software platform designed for topological data analysis in scientific visualization. TTK provides a unified, generic, efficient, and robust implementation of key algorithms for the topological analysis of scalar data, including: critical points, integral lines, persistence diagrams, persistence curves, merge trees, contour trees, Morse-Smale complexes, fiber surfaces, continuous scatterplots, Jacobi sets, Reeb spaces, and more. TTK is easily accessible to end users due to a tight integration with ParaView. It is also easily accessible to developers through a variety of bindings (Python, VTK/C++) for fast prototyping or through direct, dependence-free, C++, to ease integration into pre-existing complex systems. While developing TTK, we faced several algorithmic and software engineering challenges, which we document in this paper. In particular, we present an algorithm for the construction of a discrete gradient that complies to the critical points extracted in the piecewise-linear setting. This algorithm guarantees a combinatorial consistency across the topological abstractions supported by TTK, and importantly, a unified implementation of topological data simplification for multi-scale exploration and analysis. We also present a cached triangulation data structure, that supports time efficient and generic traversals, which self-adjusts its memory usage on demand for input simplicial meshes and which implicitly emulates a triangulation for regular grids with no memory overhead. Finally, we describe an original software architecture, which guarantees memory efficient and direct accesses to TTK features, while still allowing for researchers powerful and easy bindings and extensions. TTK is open source (BSD license) and its code, online documentation and video tutorials are available on TTK's website

    Curve reconstruction based on the relative neighbourhood graph.

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    Metric systolicity and two-dimensional Artin groups

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    We introduce the notion of metrically systolic simplicial complexes. We study geometric and large-scale properties of such complexes and of groups acting on them geometrically. We show that all two-dimensional Artin groups act geometrically on metrically systolic complexes. As direct corollaries we obtain new results on two-dimensional Artin groups and all their finitely presented subgroups: we prove that the Conjugacy Problem is solvable, and that the Dehn function is quadratic. We also show several large-scale features of finitely presented subgroups of two-dimensional Artin groups, lying background for further studies concerning their quasi-isometric rigidity.Comment: final preprint version, to appear in Math. An

    Cuneiform Detection in Vectorized Raster Images

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    Documents written in cuneiform script are one of the largest sources about ancient history. The script is written by imprinting wedges (Latin: cunei) into clay tablets and was used for almost four millennia. This three-dimensional script is typically transcribed by hand with ink on paper. These transcriptions are available in large quantities as raster graphics by online sources like the Cuneiform Database Library Initative (CDLI). Within this article we present an approach to extract Scalable Vector Graphics (SVG) in 2D from raster images as we previously did from 3D models. This enlarges our basis of data sets for tasks like word-spotting. In the first step of vectorizing the raster images we extract smooth outlines and a minimal graph representation of sets of wedges, i.e., main components of cuneiform characters. Then we discretize these outlines followed by a Delaunay triangulation to extract skeletons of sets of connected wedges. To separate the sets into single wedges we experimented with different conflict resolution strategies and candidate pruning. A thorough evaluation of our methods and its parameters on real word data shows that the wedges are extracted with a true positive rate of 0.98. At the same time the false positive rate is 0.2, which requires future extension by using statistics about geometric configurations of wedge sets

    Squarepants in a Tree: Sum of Subtree Clustering and Hyperbolic Pants Decomposition

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    We provide efficient constant factor approximation algorithms for the problems of finding a hierarchical clustering of a point set in any metric space, minimizing the sum of minimimum spanning tree lengths within each cluster, and in the hyperbolic or Euclidean planes, minimizing the sum of cluster perimeters. Our algorithms for the hyperbolic and Euclidean planes can also be used to provide a pants decomposition, that is, a set of disjoint simple closed curves partitioning the plane minus the input points into subsets with exactly three boundary components, with approximately minimum total length. In the Euclidean case, these curves are squares; in the hyperbolic case, they combine our Euclidean square pants decomposition with our tree clustering method for general metric spaces.Comment: 22 pages, 14 figures. This version replaces the proof of what is now Lemma 5.2, as the previous proof was erroneou

    Courbure discrète : théorie et applications

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    International audienceThe present volume contains the proceedings of the 2013 Meeting on discrete curvature, held at CIRM, Luminy, France. The aim of this meeting was to bring together researchers from various backgrounds, ranging from mathematics to computer science, with a focus on both theory and applications. With 27 invited talks and 8 posters, the conference attracted 70 researchers from all over the world. The challenge of finding a common ground on the topic of discrete curvature was met with success, and these proceedings are a testimony of this wor

    Robust Feature Classification and Editing

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