Abstract
Extraction, organization and exploitation of topological features are emerging topics in computer vision and graphics. However, such kind of features often exhibits weak robustness with respect to small perturbations and it is often unclear how to distinguish truly topological features from topological noise. In this paper, we present an introduction to persistence theory, which aims at analyzing multi-scale representations from a topological point of view. Besides, we extend the ideas of persistency to a more general setting by defining a set of discrete invariants.
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Moroni, D., Salvetti, M., Salvetti, O. (2008). Multi-scale Representation and Persistency for Shape Description. In: Perner, P., Salvetti, O. (eds) Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry. MDA 2008. Lecture Notes in Computer Science(), vol 5108. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70715-8_11
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DOI: https://doi.org/10.1007/978-3-540-70715-8_11
Publisher Name: Springer, Berlin, Heidelberg
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