Combinatorial curve reconstruction in Hilbert spaces: A new sampling theory and an old result revisited

The goals of this paper are twofold. The first is to present a new sampling theory for curves, based on a new notion of local feature size. The properties of this new feature size are investigated, and are compared with the standard feature size definitions. The second goal is to revisit an existing algorithm for combinatorial curve reconstruction in spaces of arbitrary dimension, the Nearest Neighbour Crust of Dey and Kumar [Proc. ACM-SIAM Sympos. Discrete Algorithms, 1999, pp. 893

• Type: Journal
• Year: 2002
• Where: COMGEO
• Authors: Daniel Freedman
• Keywords: ACM-SIAM Sympos, Applied Computing, COMGEO 2002, Discrete Algorithms, Feature Size