Stratification learning: Detecting mixed density and dimensionality in high dimensional point clouds

Journal Article

The study of point cloud data sampled from a stratification, a collection of manifolds with possible different dimensions, is pursued in this paper. We present a technique for simultaneously soft clustering and estimating the mixed dimensionality and density of such structures. The framework is based on a maximum likelihood estimation of a Poisson mixture model. The presentation of the approach is completed with artificial and real examples demonstrating the importance of extending manifold learning to stratification learning.

Duke Authors

Cited Authors

  • Haro, G; Randall, G; Sapiro, G

Published Date

  • 2007

Published In

Start / End Page

  • 553 - 560

International Standard Serial Number (ISSN)

  • 1049-5258