Robust automatic data decomposition using a modified sparse NMF

Authors:
Oksana Samko;Paul L. Rosin;A. Dave Marshall
Affiliations:
School of Computer Science, Cardiff University, UK;School of Computer Science, Cardiff University, UK;School of Computer Science, Cardiff University, UK
Venue:
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Year:
2007

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Abstract

In this paper, we address the problem of automating the partial representation from real world data with an unknown a priori structure. Such representation could be very useful for the further construction of an automatic hierarchical data model. We propose a three stage process using data normalisation and the data intrinsic dimensionality estimation as the first step. The second stage uses a modified sparse Non-negative matrix factorization (sparse NMF) algorithm to perform the initial segmentation. At the final stage region growing algorithm is applied to construct a mask of the original data. Our algorithm has a very broad range of a potential applications, we illustrate this versatility by applying the algorithm to several dissimilar data sets.