TopoInVis2022 Honorable Mention Award für „Reduced Connectivity for Local Bilinear Jacobi Sets“

Auf dem diesjjährigen IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis2022) haben Daniel Klötzl, Tim Krake, Youjia Zhou, Jonathan Stober, Kathrin Schulte, Ingrid Hotz, Bei Wang und Daniel Weiskopf den Honorable Mention Award für ihre Publikation "Reduced Connectivity for Local Bilinear Jacobi Sets" erhalten. Der TopoInVis Workshop fand in Verbindung mit der IEEE VIS 2022 in Oklahoma City, USA, statt.

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.

• Michael Sedlmair und Team erhalten den Ten Year Test of Time Award der IEEE VIS Konferenz 2022
• IEEE VIS 2022 Best Paper Award für "Uncertainty-Aware Multidimensional Scaling"