The theory of multidimensional persistent homology was initially developed in the discrete setting, and involved the study of simplicial complexes filtered through an ordering of the simplices. Later, stability properties of multidimensional persistence have been proved to hold when topological spaces are filtered by continuous functions, i.e. for continuous data. This paper aims to provide a bridge between the continuous setting, where stability properties hold, and the discrete setting, where actual computations are carried out. More precisely, a stability preserving method is developed to compare the rank invariants of vector functions obtained from discrete data. These advances confirm that multidimensional persistent homology is an appropriate tool for shape comparison in computer vision and computer graphics applications. The results are supported by numerical tests.

Comparison of persistent homologies for vector functions: from continuous to discrete and back / N. Cavazza; M. Ethier; P. Frosini; T. Kaczynski; C. Landi. - In: COMPUTERS & MATHEMATICS WITH APPLICATIONS. - ISSN 0898-1221. - STAMPA. - 66:4(2013), pp. 560-573. [10.1016/j.camwa.2013.06.004]

Comparison of persistent homologies for vector functions: from continuous to discrete and back

FROSINI, PATRIZIO;LANDI, CLAUDIA
2013

Abstract

The theory of multidimensional persistent homology was initially developed in the discrete setting, and involved the study of simplicial complexes filtered through an ordering of the simplices. Later, stability properties of multidimensional persistence have been proved to hold when topological spaces are filtered by continuous functions, i.e. for continuous data. This paper aims to provide a bridge between the continuous setting, where stability properties hold, and the discrete setting, where actual computations are carried out. More precisely, a stability preserving method is developed to compare the rank invariants of vector functions obtained from discrete data. These advances confirm that multidimensional persistent homology is an appropriate tool for shape comparison in computer vision and computer graphics applications. The results are supported by numerical tests.
2013
Comparison of persistent homologies for vector functions: from continuous to discrete and back / N. Cavazza; M. Ethier; P. Frosini; T. Kaczynski; C. Landi. - In: COMPUTERS & MATHEMATICS WITH APPLICATIONS. - ISSN 0898-1221. - STAMPA. - 66:4(2013), pp. 560-573. [10.1016/j.camwa.2013.06.004]
N. Cavazza; M. Ethier; P. Frosini; T. Kaczynski; C. Landi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/166651
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