We propose a novel method for the computation of Jacobi sets in 2D domains. The Jacobi set is a topological descriptor based on Morse theory that captures gradient alignments among multiple scalar fields, which is useful for multi-field visualization. Previous Jacobi set computations use piecewise linear approximations on triangulations that result in discretization artifacts like zig-zag patterns. In this paper, we utilize a local bilinear method to obtain a more precise approximation of Jacobi sets by preserving the topology and improving the geometry. Consequently, zig-zag patterns on edges are avoided, resulting in a smoother Jacobi set representation. Our experiments show a better convergence with increasing resolution compared to the piecewise linear method. We utilize this advantage with an efficient local subdivision scheme. Finally, our approach is evaluated qualitatively and quantitatively in comparison with previous methods for different mesh resolutions and across a number of synthetic and real-world examples.
%0 Journal Article
%1 klotzl2022local
%A Klötzl, Daniel
%A Krake, Tim
%A Zhou, Youjia
%A Hotz, Ingrid
%A Wang, Bei
%A Weiskopf, Daniel
%D 2022
%J The Visual Computer
%K myown visus:weiskopf dropit visus:kloetzdl 2022 from:kloetzdl visus visus:kraketm
%P 3435–3448
%R 10.1007/s00371-022-02557-4
%T Local bilinear computation of Jacobi sets
%U https://doi.org/10.1007/s00371-022-02557-4
%V 38
%X We propose a novel method for the computation of Jacobi sets in 2D domains. The Jacobi set is a topological descriptor based on Morse theory that captures gradient alignments among multiple scalar fields, which is useful for multi-field visualization. Previous Jacobi set computations use piecewise linear approximations on triangulations that result in discretization artifacts like zig-zag patterns. In this paper, we utilize a local bilinear method to obtain a more precise approximation of Jacobi sets by preserving the topology and improving the geometry. Consequently, zig-zag patterns on edges are avoided, resulting in a smoother Jacobi set representation. Our experiments show a better convergence with increasing resolution compared to the piecewise linear method. We utilize this advantage with an efficient local subdivision scheme. Finally, our approach is evaluated qualitatively and quantitatively in comparison with previous methods for different mesh resolutions and across a number of synthetic and real-world examples.
@article{klotzl2022local,
abstract = {We propose a novel method for the computation of Jacobi sets in 2D domains. The Jacobi set is a topological descriptor based on Morse theory that captures gradient alignments among multiple scalar fields, which is useful for multi-field visualization. Previous Jacobi set computations use piecewise linear approximations on triangulations that result in discretization artifacts like zig-zag patterns. In this paper, we utilize a local bilinear method to obtain a more precise approximation of Jacobi sets by preserving the topology and improving the geometry. Consequently, zig-zag patterns on edges are avoided, resulting in a smoother Jacobi set representation. Our experiments show a better convergence with increasing resolution compared to the piecewise linear method. We utilize this advantage with an efficient local subdivision scheme. Finally, our approach is evaluated qualitatively and quantitatively in comparison with previous methods for different mesh resolutions and across a number of synthetic and real-world examples.},
added-at = {2022-09-20T12:08:13.000+0200},
author = {Klötzl, Daniel and Krake, Tim and Zhou, Youjia and Hotz, Ingrid and Wang, Bei and Weiskopf, Daniel},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/20075822731f3a8c42321d4b3c7901750/visus},
doi = {10.1007/s00371-022-02557-4},
interhash = {b717b3a66179167a6b4c23e1fd8528c5},
intrahash = {0075822731f3a8c42321d4b3c7901750},
issn = {14322315},
journal = {The Visual Computer},
keywords = {myown visus:weiskopf dropit visus:kloetzdl 2022 from:kloetzdl visus visus:kraketm},
pages = {3435–3448},
refid = {Klötzl2022},
timestamp = {2022-09-20T10:08:43.000+0200},
title = {Local bilinear computation of Jacobi sets},
url = {https://doi.org/10.1007/s00371-022-02557-4},
volume = 38,
year = 2022
}