Implicit Surface Modelling with a Globally Regularised Basis of Compact Support

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dc.contributor.authorWalder, C.en_US
dc.contributor.authorSchoelkopf, B.en_US
dc.contributor.authorChapelle, O.en_US
dc.date.accessioned2015-02-21T14:32:15Z
dc.date.available2015-02-21T14:32:15Z
dc.date.issued2006en_US
dc.description.abstractWe consider the problem of constructing a globally smooth analytic function that represents a surface implicitly by way of its zero set, given sample points with surface normal vectors.The contributions of the paper include a novel means of regularising multi-scale compactly supported basis functions that leads to the desirable interpolation properties previously only associated with fully supported bases. We also provide a regularisation framework for simpler and more direct treatment of surface normals, along with a corresponding generalisation of the representer theorem lying at the core of kernel-based machine learning methods.We demonstrate the techniques on 3D problems of up to 14 million data points, as well as 4D time series data and four-dimensional interpolation between three-dimensional shapes.Categories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Curve, surface, solid, and object representationsen_US
dc.description.number3en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume25en_US
dc.identifier.doi10.1111/j.1467-8659.2006.00983.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages635-644en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2006.00983.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing, Incen_US
dc.titleImplicit Surface Modelling with a Globally Regularised Basis of Compact Supporten_US
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