Kernel Methods for Implicit Surface Modeling
Joachim Giesen, Simon Spalinger, Bernhard Schölkopf · Neural Information Processing Systems · 2004
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 determining regions in terms of hyperplanes.