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Persistent Homology Computation Using Combinatorial Map Simplification

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Computational Topology in Image Context (CTIC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11382))

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Abstract

We propose an algorithm for persistence homology computation of orientable 2-dimensional (2D) manifolds with or without boundary (meshes) represented by 2D combinatorial maps. Having as an input a real function h on the vertices of the mesh, we first compute persistent homology of filtrations obtained by adding cells incident to each vertex of the mesh, The cells to add are controlled by both the function h and a parameter \(\delta \). The parameter \(\delta \) is used to control the number of cells added to each level of the filtration. Bigger \(\delta \) produces less levels in the filtration and consequently more cells in each level. We then simplify each level (cluster) by merging faces of the same cluster. Our experiments demonstrate that our method allows fast computation of persistent homology of big meshes and it is persistent-homology aware in the sense that persistent homology does not change in the simplification process when fixing \(\delta \).

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Notes

  1. 1.

    The \(L_{\infty }\)-distance between points \(u = (u_1, u_2)\) and \(v = (v_1, v_2)\) in the extended plane is \( \max \{|u_1 - v_1|, |u_2 - v_2|\}\).

  2. 2.

    https://cran.r-project.org/web/packages/TDA/vignettes/article.pdf.

References

  1. Dey, T.K., Edelsbrunner, H., Guha, S.: Computational topology. In: Advances in Discrete and Computational Geometry. American Mathematical Society, pp. 109–143 (1999)

    Google Scholar 

  2. Bern, M.W., et al.: Emerging challenges in computational topology, CoRR cs.CG/9909001

    Google Scholar 

  3. Carlsson, G.: Topology and data. Bull. Am. Math. Soc. 46(2), 255–308 (1999)

    Article  MathSciNet  Google Scholar 

  4. Edelsbrunner, H., Harer, J.: Computational Topology - An Introduction. American Mathematical Society (2010)

    Google Scholar 

  5. Günther, D., Reininghaus, J., Wagner, H., Hotz, I.: Efficient computation of 3D Morse-Smale complexes and persistent homology using discrete Morse theory. Vis. Comput. 28(10), 959–969 (2012)

    Article  Google Scholar 

  6. Robins, V., Wood, P., Sheppard, A.: Theory and algorithms for constructing discrete morse complexes from grayscale digital images. IEEE Trans. Pattern Anal. Mach. Intell. 33(8), 1646–1658 (2011)

    Article  Google Scholar 

  7. Damiand, G., Gonzalez-Diaz, R.: Parallel homology computation of meshes. In: Bac, A., Mari, J.-L. (eds.) CTIC 2016. LNCS, vol. 9667, pp. 53–64. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-39441-1_6

    Chapter  Google Scholar 

  8. Lienhardt, P.: N-dimensional generalized combinatorial maps and cellular quasi-manifolds. Int. J. Comput. Geom. Appl. 4(3), 275–324 (1994)

    Article  MathSciNet  Google Scholar 

  9. Damiand, G., Lienhardt, P.: Combinatorial Maps: Efficient Data Structures for Computer Graphics and Image Processing. A. K Peters/CRC Press (2014)

    Google Scholar 

  10. Damiand, G., Peltier, S., Fuchs, L.: Computing homology for surfaces with generalized maps: application to 3D images. In: Bebis, G., et al. (eds.) ISVC 2006. LNCS, vol. 4292, pp. 235–244. Springer, Heidelberg (2006). https://doi.org/10.1007/11919629_25

    Chapter  Google Scholar 

  11. Hatcher, A.: Algebraic Topology. Cambridge University Press, Cambridge (2002)

    MATH  Google Scholar 

  12. Gonzalez-Diaz, R., Real, P.: On the cohomology of 3D digital images. Discrete Appl. Math. 147(2–3), 245–263 (2005)

    Article  MathSciNet  Google Scholar 

  13. Gonzalez-Diaz, R., Ion, A., Jimenez, M.J., Poyatos, R.: Incremental-decremental algorithm for computing AT-models and persistent homology. In: Real, P., Diaz-Pernil, D., Molina-Abril, H., Berciano, A., Kropatsch, W. (eds.) CAIP 2011. LNCS, vol. 6854, pp. 286–293. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-23672-3_35

    Chapter  Google Scholar 

  14. Damiand, G.: Combinatorial maps. In: CGAL User and Reference Manual, 3.9 edn (2011). http://www.cgal.org/Pkg/CombinatorialMaps

  15. Damiand, G.: Linear cell complex. In: CGAL User and Reference Manual, 4.0 edn (2012). http://www.cgal.org/Pkg/LinearCellComplex

  16. Damiand, G., Gonzalez-Diaz, R., Peltier, S.: Removal operations in nD generalized maps for efficient homology computation. In: Ferri, M., Frosini, P., Landi, C., Cerri, A., Di Fabio, B. (eds.) CTIC 2012. LNCS, vol. 7309, pp. 20–29. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-30238-1_3

    Chapter  MATH  Google Scholar 

  17. Damiand, G., Gonzalez-Diaz, R., Peltier, S.: Removal and contraction operations in nD generalized maps for efficient homology computation, CoRR abs/1403.3683

    Google Scholar 

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Acknowledgments

This research has been partially supported by MINECO, FEDER/UE under grant MTM2015-67072-P. We thank the anonymous reviewers for their valuable comments.

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Correspondence to Guillaume Damiand .

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Damiand, G., Gonzalez-Diaz, R. (2019). Persistent Homology Computation Using Combinatorial Map Simplification. In: Marfil, R., Calderón, M., Díaz del Río, F., Real, P., Bandera, A. (eds) Computational Topology in Image Context. CTIC 2019. Lecture Notes in Computer Science(), vol 11382. Springer, Cham. https://doi.org/10.1007/978-3-030-10828-1_3

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  • DOI: https://doi.org/10.1007/978-3-030-10828-1_3

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