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dc.contributor.authorBorn, Janisen_US
dc.contributor.authorSchmidt, Patricken_US
dc.contributor.authorCampen, Marcelen_US
dc.contributor.authorKobbelt, Leifen_US
dc.contributor.editorDigne, Julie and Crane, Keenanen_US
dc.date.accessioned2021-07-10T07:46:26Z
dc.date.available2021-07-10T07:46:26Z
dc.date.issued2021
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14367
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14367
dc.description.abstractA homeomorphism between two surfaces not only defines a (continuous and bijective) geometric correspondence of points but also (by implication) an identification of topological features, i.e. handles and tunnels, and how the map twists around them. However, in practice, surface maps are often encoded via sparse correspondences or fuzzy representations that merely approximate a homeomorphism and are therefore inherently ambiguous about map topology. In this work, we show a way to infer topological information from an imperfect input map between two shapes. In particular, we compute a homology map, a linear map that transports homology classes of cycles from one surface to the other, subject to a global consistency constraint. Our inference robustly handles imperfect (e.g., partial, sparse, fuzzy, noisy, outlier-ridden, non-injective) input maps and is guaranteed to produce homology maps that are compatible with true homeomorphisms between the input shapes. Homology maps inferred by our method can be directly used to transfer homological information between shapes, or serve as foundation for the construction of a proper homeomorphism guided by the input map, e.g., via compatible surface decomposition.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectComputing methodologies
dc.subjectShape modeling
dc.titleSurface Map Homology Inferenceen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersDirection Fields and Quads
dc.description.volume40
dc.description.number5
dc.identifier.doi10.1111/cgf.14367
dc.identifier.pages193-203


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  • 40-Issue 5
    Geometry Processing 2021 - Symposium Proceedings

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