A variant of adaptive mean shift-based clustering

Authors:
Fajie Li;Reinhard Klette
Affiliations:
University of Groningen, The Netherlands;The University of Auckland, New Zealand
Venue:
ICONIP'08 Proceedings of the 15th international conference on Advances in neuro-information processing - Volume Part I
Year:
2008

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Abstract

This paper proposes a special adaptive mean shift clustering algorithm, especially for the case of highly overlapping clusters. Its application is demonstrated for simulated data, aiming at finding the 'old clusters'. The obtained clustering result is actually close to an estimated upper bound, derived for those simulated data elsewhere.