Skip to main content

Advertisement

Springer Nature Link
Log in
Menu
Find a journal Publish with us Track your research
Search
Saved research
Cart
  1. Home
  2. Discrete Geometry for Computer Imagery
  3. Conference paper

The Persistence Space in Multidimensional Persistent Homology

  • Conference paper
  • pp 180–191
  • Cite this conference paper
Save conference paper
View saved research
Discrete Geometry for Computer Imagery (DGCI 2013)
The Persistence Space in Multidimensional Persistent Homology
  • Andrea Cerri18,20 &
  • Claudia Landi19,20 

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 7749))

Included in the following conference series:

  • International Conference on Discrete Geometry for Computer Imagery
  • 2608 Accesses

  • 14 Citations

  • 3 Altmetric

Abstract

Multidimensional persistent modules do not admit a concise representation analogous to that provided by persistence diagrams for real-valued functions. However, there is no obstruction for multidimensional persistent Betti numbers to admit one. Therefore, it is reasonable to look for a generalization of persistence diagrams concerning those properties that are related only to persistent Betti numbers. In this paper, the persistence space of a vector-valued continuous function is introduced to generalize the concept of persistence diagram in this sense. Furthermore, it is presented a method to visualize topological features of a shape via persistence spaces. Finally, it is shown that this method is resistant to perturbations of the input data.

Download to read the full chapter text

Chapter PDF

Similar content being viewed by others

On the Space of Generalized Persistence Diagrams

Chapter © 2025

Topological and metric properties of spaces of generalized persistence diagrams

Article 23 January 2024

On the geometrical properties of the coherent matching distance in 2D persistent homology

Article 07 September 2019

Explore related subjects

Discover the latest articles, books and news in related subjects, suggested using machine learning.
  • Data Storage Representation
  • Manifolds and Cell Complexes
  • Multilinear Algebra
  • Algebraic Topology
  • Category Theory, Homological Algebra
  • Topology
  • Topological Data Analysis in Complex Systems

References

  1. Biasotti, S., Bai, X., Bustos, B., Cerri, A., Giorgi, D., Li, L., Mortara, M., Sipiran, I., Zhang, S., Spagnuolo, M.: SHREC’12 Track: Stability on Abstract Shapes, pp. 101–107. Eurographics Association, Cagliari (2012)

    Google Scholar 

  2. Biasotti, S., De Floriani, L., Falcidieno, B., Frosini, P., Giorgi, D., Landi, C., Papaleo, L., Spagnuolo, M.: Describing shapes by geometrical-topological properties of real functions. ACM Comput. Surv. 40(4), 1–87 (2008)

    Article  Google Scholar 

  3. Bronstein, A., Bronstein, M., Kimmel, R.: Numerical Geometry of Non-Rigid Shapes, 1st edn. Springer Publishing Company, Incorporated (2008)

    Google Scholar 

  4. Cagliari, F., Di Fabio, B., Ferri, M.: One-dimensional reduction of multidimensional persistent homology. Proc. Amer. Math. Soc. 138, 3003–3017 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  5. Cagliari, F., Landi, C.: Finiteness of rank invariants of multidimensional persistent homology groups. Appl. Math. Lett. 24(4), 516–518 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  6. Carlsson, G., Zomorodian, A.: The theory of multidimensional persistence. Discr. Comput. Geom. 42(1), 71–93 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  7. Cavazza, N., Ethier, M., Frosini, P., Kaczynski, T., Landi, C.: Comparison of persistent homologies for vector functions: from continuous to discrete and back (2012), http://arxiv.org/abs/1201.3217

  8. Cerri, A., Di Fabio, B., Ferri, M., Frosini, P., Landi, C.: Betti numbers in multidimensional persistent homology are stable functions. Math. Method. Appl. Sci. (in press), doi:10.1002/mma.2704

    Google Scholar 

  9. Cerri, A., Landi, C.: Persistence space of vector-valued continuous functions, manuscript, http://www.dm.unibo.it/~cerri/Publications.html

  10. Chazal, F., Cohen-Steiner, D., Guibas, L.J., Mémoli, F., Oudot, S.: Gromov-Hausdorff stable signatures for shapes using persistence. Computer Graphics Forum 28(5), 1393–1403 (2009)

    Article  Google Scholar 

  11. Chen, C., Freedman, D.: Topology Noise Removal for Curve and Surface Evolution. In: Menze, B., Langs, G., Tu, Z., Criminisi, A. (eds.) MICCAI 2010 Workshop MCV. LNCS, vol. 6533, pp. 31–42. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  12. Cohen-Steiner, D., Edelsbrunner, H., Harer, J.: Stability of persistence diagrams. Discr. Comput. Geom. 37(1), 103–120 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  13. Edelsbrunner, H., Harer, J.: Computational Topology: An Introduction. American Mathematical Society (2009)

    Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  15. Edelsbrunner, H., Symonova, O.: The adaptive topology of a digital image. In: 2012 Ninth International Symposium on Voronoi Diagrams in Science and Engineering (ISVD), pp. 41–48 (2012)

    Google Scholar 

  16. Frosini, P., Landi, C.: Size functions and formal series. Appl. Algebra Engrg. Comm. Comput. 12(4), 327–349 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  17. Frosini, P., Landi, C.: Size theory as a topological tool for computer vision. Pattern Recogn. and Image Anal. 9, 596–603 (1999)

    Google Scholar 

  18. Frosini, P., Mulazzani, M.: Size homotopy groups for computation of natural size distances. Bulletin of the Belgian Mathematical Society 6(3), 455–464 (1999)

    MathSciNet  MATH  Google Scholar 

  19. Letscher, D., Fritts, J.: Image Segmentation Using Topological Persistence. In: Kropatsch, W.G., Kampel, M., Hanbury, A. (eds.) CAIP 2007. LNCS, vol. 4673, pp. 587–595. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  20. Paris, S., Durand, F.: A topological approach to hierarchical segmentation using mean shift. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007, pp. 1–8 (2007)

    Google Scholar 

  21. Pascucci, V., Tricoche, X., Hagen, H., Tierny, J. (eds.): Topological Methods in Data Analysis and Visualization. Mathematics and Visualization. Springer (2011)

    Google Scholar 

  22. Rieck, B., Mara, H., Leitte, H.: Multivariate data analysis using persistence-based filtering and topological signatures. IEEE Transactions on Visualization and Computer Graphics 18, 2382–2391 (2012)

    Article  Google Scholar 

  23. Robins, V., Wood, P.J., Sheppard, A.P.: 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 

  24. Smeulders, A., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE Trans. PAMI 22(12) (2000)

    Google Scholar 

  25. Tangelder, J., Veltkamp, R.: A survey of content-based 3D shape retrieval methods. Multimedia Tools and Applications 39(3), 441–471 (2008)

    Article  Google Scholar 

  26. Verri, A., Uras, C., Frosini, P., Ferri, M.: On the use of size functions for shape analysis. Biol. Cybern. 70, 99–107 (1993)

    Article  MATH  Google Scholar 

  27. Zheng, Y., Gu, S., Edelsbrunner, H., Tomasi, C., Benfey, P.: Detailed reconstruction of 3D plant root shape. In: Metaxas, D.N., Quan, L., Sanfeliu, A., Gool, L.J.V. (eds.) ICCV, pp. 2026–2033. IEEE (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. IMATI – CNR, Genova, Italia

    Andrea Cerri

  2. DISMI, Università di Modena e Reggio Emilia, Italia

    Claudia Landi

  3. ARCES, Università di Bologna, Italia

    Andrea Cerri & Claudia Landi

Authors
  1. Andrea Cerri
    View author publications

    Search author on:PubMed Google Scholar

  2. Claudia Landi
    View author publications

    Search author on:PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Applied Math I, University of Seville, Avd. Reina Mercedes s/n, 41012, Seville, Spain

    Rocio Gonzalez-Diaz & Maria-Jose Jimenez & 

  2. Applied Math I, University of Seville, Avd. Reina Mercedes s/n, 41012, Seville, Spain

    Belen Medrano

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Cerri, A., Landi, C. (2013). The Persistence Space in Multidimensional Persistent Homology. In: Gonzalez-Diaz, R., Jimenez, MJ., Medrano, B. (eds) Discrete Geometry for Computer Imagery. DGCI 2013. Lecture Notes in Computer Science, vol 7749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37067-0_16

Download citation

  • .RIS
  • .ENW
  • .BIB
  • DOI: https://doi.org/10.1007/978-3-642-37067-0_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37066-3

  • Online ISBN: 978-3-642-37067-0

  • eBook Packages: Computer ScienceComputer Science (R0)Springer Nature Proceedings Computer Science

Share this paper

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Topological Feature
  • Homology Class
  • Lower Dimensional Space
  • Persistent Homology
  • Multidimensional Analogue

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Publish with us

Policies and ethics

Profiles

  1. Claudia Landi View author profile

Societies and partnerships

  • The International Association for Pattern Recognition
    The International Association for Pattern Recognition (opens in a new tab)

Search

Navigation

  • Find a journal
  • Publish with us
  • Track your research

Footer Navigation

Discover content

  • Journals A-Z
  • Books A-Z
  • Subjects A-Z

Publish with us

  • Journal finder
  • Publish your research
  • Language editing
  • Open access publishing

Products and services

  • Our products
  • Librarians
  • Societies
  • Partners and advertisers

Our brands

  • Springer
  • Nature Portfolio
  • BMC
  • Palgrave Macmillan
  • Apress
  • Discover

Corporate Navigation

  • Your US state privacy rights
  • Accessibility statement
  • Terms and conditions
  • Privacy policy
  • Help and support
  • Legal notice
  • Cancel contracts here

3.66.179.167

Not affiliated

Springer Nature

© 2026 Springer Nature