Hermite Radial Basis Functions Implicits

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dc.contributor.authorMacedo, I.en_US
dc.contributor.authorGois, J. P.en_US
dc.contributor.authorVelho, L.en_US
dc.contributor.editorEduard Groeller and Holly Rushmeieren_US
dc.date.accessioned2015-02-27T10:19:08Z
dc.date.available2015-02-27T10:19:08Z
dc.date.issued2011en_US
dc.description.abstractThe Hermite radial basis functions (HRBF) implicits reconstruct an implicit function which interpolates or approximates scattered multivariate Hermite data (i.e. unstructured points and their corresponding normals). Experiments suggest that HRBF implicits allow the reconstruction of surfaces rich in details and behave better than previous related methods under coarse and/or non-uniform samplings, even in the presence of close sheets. HRBF implicits theory unifies a recently introduced class of surface reconstruction methods based on radial basis functions (RBF), which incorporate normals directly in their problem formulation. Such class has the advantage of not depending on manufactured offset-points to ensure existence of a non-trivial implicit surface RBF interpolant. In fact, we show that HRBF implicits constitute a particular case of Hermite–Birkhoff interpolation with radial basis functions, whose main results we present here. This framework not only allows us to show connections between the present method and others but also enable us to enhance the flexibility of our method by ensuring well-posedness of an interesting combined interpolation/regularization approach.en_US
dc.description.number1
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume30
dc.identifier.doi10.1111/j.1467-8659.2010.01785.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2010.01785.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleHermite Radial Basis Functions Implicitsen_US
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