Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Jacobi set simplification for tracking topological features in time-varying scalar fields

  • Research
  • Published:
The Visual Computer Aims and scope Submit manuscript

A Correction to this article was published on 27 July 2024

This article has been updated

Abstract

The Jacobi set of a bivariate scalar field is the set of points where the gradients of the two constituent scalar fields align with each other. It captures the regions of topological changes in the bivariate field. The Jacobi set is a bivariate analog of critical points, and may correspond to features of interest. In the specific case of time-varying fields and when one of the scalar fields is time, the Jacobi set corresponds to temporal tracks of critical points, and serves as a feature-tracking graph. The Jacobi set of a bivariate field or a time-varying scalar field is complex, resulting in cluttered visualizations that are difficult to analyze. This paper addresses the problem of Jacobi set simplification. Specifically, we use the time-varying scalar field scenario to introduce a method that computes a reduced Jacobi set. The method is based on a stability measure called robustness that was originally developed for vector fields and helps capture the structural stability of critical points. We also present a mathematical analysis for the method, and describe an implementation for 2D time-varying scalar fields. Applications to both synthetic and real-world datasets demonstrate the effectiveness of the method for tracking features.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

Data availability

No datasets were generated or analyzed during the current study.

Change history

References

  1. Artamonova, I., Alekseev, V., Makarenko, N.: Gradient measure and Jacobi sets for estimation of interrelationship between geophysical multifields. In: J. Phys.: Conf. Ser. 798, 012040 (2017)

    Article  Google Scholar 

  2. Ayachit, U.: The ParaView Guide. A Parallel Visualization Application, Kitware (2015)

    Google Scholar 

  3. Bachthaler, S., Weiskopf, D.: Continuous scatterplots. IEEE Trans. Vis. Comput. Graph. 14(6), 1428–1435 (2008)

    Article  Google Scholar 

  4. Bhatia, H., Wang, B., Norgard, G., Pascucci, V., Bremer, P.T.: Local, smooth, and consistent Jacobi set simplification. Comput. Geom. 48(4), 311–332 (2015)

    Article  MathSciNet  Google Scholar 

  5. Blecha, C., Raith, F., Scheuermann, G., Nagel, T., Kolditz, O., Maßmann, J.: Analysis of coupled thermo-hydro-mechanical simulations of a generic nuclear waste repository in clay rock using fiber surfaces. In: IEEE Pacific Visualization Symposium, pp. 189–201 (2019)

  6. Bremer, P., Bringa, E., Duchaineau, M., Gyulassy, A., Laney, D., Mascarenhas, A., Pascucci, V.: Topological feature extraction and tracking. In: J. Phys.: Conf. Ser. 78, 012007 (2007). (IOP Publishing)

    Article  Google Scholar 

  7. Bujack, R., Yan, L., Hotz, I., Garth, C., Wang, B.: State of the art in time-dependent flow topology: interpreting physical meaningfulness through mathematical properties. Comput. Graph, Forum (2020)

    Google Scholar 

  8. Carr, H., Duke, D.: Joint contour nets. IEEE Trans. Vis. Comput. Graph. 20(8), 1100–1113 (2014)

    Article  Google Scholar 

  9. Carr, H., Geng, Z., Tierny, J., Chattopadhyay, A., Knoll, A.: Fiber surfaces: Generalizing isosurfaces to bivariate data. Comput. Graph. Forum 34(3), 241–250 (2015)

    Article  Google Scholar 

  10. Chattopadhyay, A., Carr, H., Duke, D., Geng, Z.: Extracting Jacobi structures in Reeb spaces. In: Proc. EuroVis - Short Papers (2014)

  11. Chazal, F., Patel, A., Skraba, P.: Computing the robustness of roots. Manuscript, http://ailab.ijs.si/primozskraba/papers/fp.pdf (2011)

  12. Conway, J.B.: Functions of One Complex Variable I. Graduate Texts in Mathematics. Springer, New York (2012)

    Google Scholar 

  13. Conway, J.B.: Functions of One Complex Variable II. Graduate Texts in Mathematics. Springer, New York (2012)

    Google Scholar 

  14. Copernicus Marine Service: (2024). https://marine.copernicus.eu/

  15. Delfinado, C.J.A., Edelsbrunner, H.: An incremental algorithm for betti numbers of simplicial complexes. In: Proc. Symposium on Computational Geometry, pp. 232–239 (1993)

  16. Doleisch, H., Muigg, P., Hauser, H.: Interactive visual analysis of hurricane isabel with SimVis. In: IEEE Visualization Contest (2004)

  17. Edelsbrunner, H., Harer, J.: Jacobi sets of multiple Morse functions. Found. Comput. Math. 312, 35–57 (2004)

    MathSciNet  Google Scholar 

  18. Edelsbrunner, H., Harer, J., Mascarenhas, A., Pascucci, V., Snoeyink, J.: Time-varying Reeb graphs for continuous space-time data. Comput. Geom. 41(3), 149–166 (2008)

    Article  MathSciNet  Google Scholar 

  19. Edelsbrunner, H., Harer, J., Natarajan, V., Pascucci, V.: Local and global comparison of continuous functions. In: IEEE Visualization 2004, pp. 275–280 (2004)

  20. Edelsbrunner, H., Harer, J., Patel, A.K.: Reeb spaces of piecewise linear mappings. In: Proc. Symposium on Computational Geometry, SCG ’08, p. 242-250 (2008)

  21. Edelsbrunner, H., Harer, J.L.: Computational topology: an introduction. American Mathematical Society (2022)

  22. Edelsbrunner, H., Letscher, D., Zomorodian, A.: Topological persistence and simplification. Disc. Comput. Geom. 28(4), 511–533 (2002)

    Article  MathSciNet  Google Scholar 

  23. Edelsbrunner, H., Morozov, D., Patel, A.: Quantifying transversality by measuring the robustness of intersections. Found. Comput. Math. 11(3), 345–361 (2011)

    Article  MathSciNet  Google Scholar 

  24. Edelsbrunner, H., Mücke, E.P.: Simulation of simplicity: a technique to cope with degenerate cases in geometric algorithms. ACM Trans. Gr. 9(1), 66–104 (1990)

    Article  Google Scholar 

  25. Günther, T., Gross, M., Theisel, H.: Generic objective vortices for flow visualization. ACM Trans. Gr. (Proc. SIGGRAPH) 36(4), 141:1-141:11 (2017)

    Google Scholar 

  26. Hansen, C.D., Chen, M., Johnson, C.R., Kaufman, A.E., Hagen, H. (eds.): Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization. Springer, Mathematics and Visualization (2014)

    Google Scholar 

  27. Helland-Hansen, B.: Nogen hydrografiske metoder. Forh. Skand. Naturf. Mote. 16, 357–359 (1916)

    Google Scholar 

  28. Huettenberger, L., Heine, C., Garth, C.: Decomposition and simplification of multivariate data using pareto sets. IEEE Trans. Vis. Comput. Graph. 20(12), 2684–2693 (2014)

    Article  Google Scholar 

  29. Klötzl, D., Krake, T., Zhou, Y., Hotz, I., Wang, B., Weiskopf, D.: Local bilinear computation of Jacobi sets. The Vis. Comput. 38(9–10), 3435–3448 (2022)

    Article  Google Scholar 

  30. Klötzl, D., Krake, T., Zhou, Y., Stober, J., Schulte, K., Hotz, I., Wang, B., Weiskopf, D.: Reduced connectivity for local bilinear Jacobi sets. In: 2022 Topological Data Analysis and Visualization (TopoInVis), pp. 39–48. IEEE (2022)

  31. Lukasczyk, J., Garth, C., Maciejewski, R., Tierny, J.: Localized topological simplification of scalar data. IEEE Trans. Vis. Comput. Graph. 27(2), 572–582 (2020)

    Article  Google Scholar 

  32. Lukasczyk, J., Garth, C., Weber, G.H., Biedert, T., Maciejewski, R., Leitte, H.: Dynamic nested tracking graphs. IEEE Trans. Vis. Comput. Graph. 26(1), 249–258 (2020)

    Article  Google Scholar 

  33. Lukasczyk, J., Weber, G., Maciejewski, R., Garth, C., Leitte, H.: Nested tracking graphs. Comput. Graph. Forum 36(3), 12–22 (2017)

    Google Scholar 

  34. Makela, K., Ophelders, T., Quigley, M.Y., Munch, E., Chitwood, D.H., Dowtin, A.L.: Automatic tree ring detection using Jacobi sets. arXiv:2010.08691 (2020)

  35. Nagaraj, S., Natarajan, V.: Relation-aware isosurface extraction in multifield data. IEEE Trans. Vis. Comput. Graph. 17(2), 182–191 (2011)

    Article  Google Scholar 

  36. Norgard, G., Bremer, P.T.: Ridge-Valley graphs: Combinatorial ridge detection using Jacobi sets. Comput. Aided Geom. Des. 30(6), 597–608 (2013)

    Article  MathSciNet  Google Scholar 

  37. Popinet, S.: Free computational fluid dynamics. ClusterWorld 2(6) (2004). http://gfs.sf.net/

  38. Post, F.H., Vrolijk, B., Hauser, H., Laramee, R.S., Doleisch, H.: The state of the art in flow visualisation: feature extraction and tracking. Comput. Graph. Forum 22 (2003)

  39. Raith, F., Blecha, C., Nagel, T., Parisio, F., Kolditz, O., Günther, F., Stommel, M., Scheuermann, G.: Tensor field visualization using fiber surfaces of invariant space. IEEE Trans. Vis. Comput. Graph. 25(1), 1122–1131 (2019)

    Article  Google Scholar 

  40. Reininghaus, J., Kasten, J., Weinkauf, T., Hotz, I.: Efficient computation of combinatorial feature flow fields. IEEE Trans. Vis. Comput. Graph. 18(9), 1563–1573 (2011)

    Article  Google Scholar 

  41. Saikia, H., Weinkauf, T.: Global feature tracking and similarity estimation in time-dependent scalar fields. Comput. Graph. Forum 36(3), 1–11 (2017)

    Article  Google Scholar 

  42. Sharma, M., Masood, T.B., Thygesen, S.S., Linares, M., Hotz, I., Natarajan, V.: Segmentation driven peeling for visual analysis of electronic transitions. In: Proc. IEEE Visualization Conference, IEEE VIS 2021 - Short Papers, pp. 96–100. IEEE (2021)

  43. Sharma, M., Masood, T.B., Thygesen, S.S., Linares, M., Hotz, I., Natarajan, V.: Continuous scatterplot operators for bivariate analysis and study of electronic transitions. IEEE Trans. Vis. Comput. Graph. pp. 1–13 (2023). https://doi.org/10.1109/TVCG.2023.3237768

  44. Sharma, M., Natarajan, V.: Jacobi set driven search for flexible fiber surface extraction. In: 2022 Topological Data Analysis and Visualization (TopoInVis), pp. 49–58 (2022)

  45. Skraba, P., Wang, B., Chen, G., Rosen, P.: Robustness-based simplification of 2D steady and unsteady vector fields. IEEE Trans. Vis. Comput. Graph. 21(8), 930–944 (2015)

    Article  Google Scholar 

  46. Soler, M., Plainchault, M., Conche, B., Tierny, J.: Lifted wasserstein matcher for fast and robust topology tracking. In: Proc. IEEE Symp. Large Data Anal. Vis. (LDAV), pp. 23–33 (2018)

  47. Suthambhara, N., Natarajan, V.: Simplification of Jacobi sets. In: Topological Methods in Data Analysis and Visualization: Theory. Algorithms, and Applications, pp. 91–102. Springer, Berlin Heidelberg, Berlin, Heidelberg (2011)

  48. Theisel, H., Seidel, H.P.: Feature flow fields. In: Proceedings of the symposium on Data visualisation 2003, pp. 141–148 (2003)

  49. Tierny, J., Carr, H.: Jacobi fiber surfaces for bivariate Reeb space computation. IEEE Trans. Vis. Comput. Graph. 23(1), 960–969 (2016)

    Article  Google Scholar 

  50. Tierny, J., Favelier, G., Levine, J.A., Gueunet, C., Michaux, M.: The topology toolKit. IEEE Trans. Vis. Comput. Graph. 24(1), 832–842 (2018)

    Article  Google Scholar 

  51. Tricoche, X., Wischgoll, T., Scheuermann, G., Hagen, H.: Topology tracking for the visualization of time-dependent two-dimensional flows. Comput. & Gr. 26(2), 249–257 (2002)

    Article  Google Scholar 

  52. Weinkauf, T., Theisel, H., Van Gelder, A., Pang, A.: Stable feature flow fields. IEEE Trans. Vis. Comput. Graph. 17(6), 770–780 (2011)

    Article  Google Scholar 

  53. Yan, L., Bin Masood, T., Sridharamurthy, R., Rasheed, F., Natarajan, V., Hotz, I., Wang, B.: Scalar field comparison with topological descriptors: properties and applications for scientific visualization. Comput. Graph. Forum 40, 599–633 (2021)

    Article  Google Scholar 

Download references

Acknowledgements

This work is partially supported by a grant from SERB, Govt. of India (CRG/2021/005278). VN acknowledges support from the Alexander von Humboldt Foundation, and Berlin MATH+ under the Visiting Scholar program. Part of this work was completed when VN was a guest Professor at the Zuse Institute Berlin.

Author information

Authors and Affiliations

Authors

Contributions

D.M. Methodology,Theoretical Analysis, Visualization, Software, Experiments, Writing—Original Draft, Review and Editing. M.S. Experiments, Visualization, Writing—All Illustrations, Review and Editing. V.N. Conceptualization of this study, Methodology, Writing—Review and Editing.

Corresponding author

Correspondence to Dhruv Meduri.

Ethics declarations

Conflict of interests

The authors declare no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file 1 (pdf 136 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Meduri, D., Sharma, M. & Natarajan, V. Jacobi set simplification for tracking topological features in time-varying scalar fields. Vis Comput 40, 4843–4855 (2024). https://doi.org/10.1007/s00371-024-03484-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-024-03484-2

Keywords

Navigation