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Kernel Methods for Implicit Surface Modeling

Annual Conference on Neural Information Processing Systems, (2004)

Cited: 71|Views25
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Abstract

We describe methods for computing an implicit model of a hypersurface that is given only by a finite sampling. The methods work by mapping the sample points into a reproducing kernel Hilbert space and then deter- mining regions in terms of hyperplanes.

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