DocumentCode
2163438
Title
Sampling on locally defined principal manifolds
Author
Bas, Erhan ; Erdogmus, Deniz
Author_Institution
ECE Dept., Northeastern Univ., Boston, MA, USA
fYear
2011
fDate
22-27 May 2011
Firstpage
2276
Lastpage
2279
Abstract
We start with a locally defined principal curve definition for a given probability density function (pdf) and define a pairwise manifold score based on local derivatives of the pdf. Proposed manifold score can be used to check if data pairs lie on the same manifold. We use this score to (i) cluster nonlinear manifolds having irregular shapes, and (ii) (down)sample a selected principal curve with sufficient accuracy sparsely. Our goal is to provide a heuristic-free formulation for principal graph generation and curve parametrization in order to form a basis for a principled principal manifold unwrapping method.
Keywords
pattern clustering; probability; unsupervised learning; cluster nonlinear manifold; curve parametrization; graph generation; heuristic-free formulation; principal curve definition; probability density function; Eigenvalues and eigenfunctions; Euclidean distance; Image color analysis; Indexes; Kernel; Manifolds; Probability density function; Principal graphs; resampling on manifolds;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location
Prague
ISSN
1520-6149
Print_ISBN
978-1-4577-0538-0
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2011.5946936
Filename
5946936
Link To Document