Reduced Connectivity for Local Bilinear Jacobi Sets

August 15, 2022 Β· Declared Dead Β· πŸ› 2022 Topological Data Analysis and Visualization (TopoInVis)

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Authors Daniel KlΓΆtzl, Tim Krake, Youjia Zhou, Jonathan Stober, Kathrin Schulte, Ingrid Hotz, Bei Wang, Daniel Weiskopf arXiv ID 2208.07148 Category cs.CG: Computational Geometry Cross-listed cs.HC Citations 2 Venue 2022 Topological Data Analysis and Visualization (TopoInVis) Last Checked 3 months ago
Abstract
We present a new topological connection method for the local bilinear computation of Jacobi sets that improves the visual representation while preserving the topological structure and geometric configuration. To this end, the topological structure of the local bilinear method is utilized, which is given by the nerve complex of the traditional piecewise linear method. Since the nerve complex consists of higher-dimensional simplices, the local bilinear method (visually represented by the 1-skeleton of the nerve complex) leads to clutter via crossings of line segments. Therefore, we propose a homotopy-equivalent representation that uses different collapses and edge contractions to remove such artifacts. Our new connectivity method is easy to implement, comes with only little overhead, and results in a less cluttered representation.
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