Surface Reconstruction Based on Hierarchical Floating Radial Basis Functions

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dc.contributor.authorSuessmuth, J.en_US
dc.contributor.authorMeyer, Q.en_US
dc.contributor.authorGreiner, G.en_US
dc.date.accessioned2015-02-23T09:40:42Z
dc.date.available2015-02-23T09:40:42Z
dc.date.issued2010en_US
dc.description.abstractIn this paper we address the problem of optimal centre placement for scattered data approximation using radial basis functions (RBFs) by introducing the concept of floating centres. Given an initial least-squares solution, we optimize the positions and the weights of the RBF centres by minimizing a non-linear error function. By optimizing the centre positions, we obtain better approximations with a lower number of centres, which improves the numerical stability of the fitting procedure. We combine the non-linear RBF fitting with a hierarchical domain decomposition technique. This provides a powerful tool for surface reconstruction from oriented point samples. By directly incorporating point normal vectors into the optimization process, we avoid the use of off-surface points which results in less computational overhead and reduces undesired surface artefacts. We demonstrate that the proposed surface reconstruction technique is as robust as recent methods, which compute the indicator function of the solid described by the point samples. In contrast to indicator function based methods, our method computes a global distance field that can directly be used for shape registration.en_US
dc.description.number6en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume29en_US
dc.identifier.doi10.1111/j.1467-8659.2010.01653.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages1854-1864en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2010.01653.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleSurface Reconstruction Based on Hierarchical Floating Radial Basis Functionsen_US
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