We present new sampling theorems for surfaces and higher dimensional manifolds. The core of the proofs resides in triangulation results for manifolds with boundary, not necessarily...
Manifold learning can discover the structure of high dimensional data and provides understanding of multidimensional patterns by preserving the local geometric characteristics. Ho...
This paper presents a novel approach for surface reconstruction from point clouds. The proposed technique is general in the sense that it naturally handles both manifold and non-m...
Jianning Wang, Manuel M. Oliveira, Arie E. Kaufman
We present a fast, memory efficient algorithm that generates a manifold triangular mesh S passing through a set of unorganized points P R3 . Nothing is assumed about the geometry,...
We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...