Morse Complexes for Shape Segmentation and Homological Analysis: Discrete Models and Algorithms

dc.contributor.authorFloriani, Leila Deen_US
dc.contributor.authorFugacci, Uldericoen_US
dc.contributor.authorIuricich, Federicoen_US
dc.contributor.authorMagillo, Paolaen_US
dc.contributor.editorK. Hormann and O. Staadten_US
dc.date.accessioned2015-04-16T06:15:24Z
dc.date.available2015-04-16T06:15:24Z
dc.date.issued2015en_US
dc.description.abstractMorse theory offers a natural and mathematically-sound tool for shape analysis and understanding. It allows studying the behavior of a scalar field defined on a manifold. Starting from a Morse function, we can decompose the domain of the function into meaningful regions associated with the critical points of the field. Such decompositions, called Morse complexes, provide a segmentation of a shape and are extensively used in terrain modeling and in scientific visualization. Discrete Morse theory, a combinatorial counterpart of smooth Morse theory defined over cell complexes, provides an excellent basis for computing Morse complexes in a robust and efficient way. Moreover, since a discrete Morse complex computed over a given complex has the same homology as the original one, but fewer cells, discrete Morse theory is a fundamental tool for detecting holes efficiently in shapes through homology and persistent homology. In this survey, we review, classify and analyze algorithms for computing and simplifying Morse complexes in the context of such applications with an emphasis on discrete Morse theory and on algorithms based on it.en_US
dc.description.documenttypestar
dc.description.number2en_US
dc.description.sectionheadersState of the Art Reportsen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume34en_US
dc.identifier.doi10.1111/cgf.12596en_US
dc.identifier.pages761-785en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12596en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.titleMorse Complexes for Shape Segmentation and Homological Analysis: Discrete Models and Algorithmsen_US
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