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Quick shift and kernel methods for mode seeking

Abstract:

We show that the complexity of the recently introduced medoid-shift algorithm in clustering N points is O(N 2), with a small constant, if the underlying distance is Euclidean. This makes medoid shift considerably faster than mean shift, contrarily to what previously believed. We then exploit kernel methods to extend both mean shift and the improved medoid shift to a large family of distances, with complexity bounded by the effective rank of the resulting kernel matrix...

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Authors


Vedaldi, A More by this author
Journal:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume:
5305 LNCS
Issue:
PART 4
Pages:
705-718
Publication date:
2008
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
URN:
uuid:24d780fa-1f14-46e4-985b-278e6bcb4c3b
Source identifiers:
293256
Local pid:
pubs:293256
Language:
English

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