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Anchorage, AK, USA
June 23, 2008 to June 28, 2008
ISBN: 978-1-4244-2339-2
pp: 1-6
Longbin Chen , Computer Sciences, UC, Santa Barbara, USA
Rogerio Feris , Exploratory Computer Vision, IBM T.J. Watson Research, USA
Matthew Turk , Computer Sciences, UC, Santa Barbara, USA
ABSTRACT
This paper presents an efficient partial shape matching method based on the Smith-Waterman algorithm. For two contours of m and n points respectively, the complexity of our method to find similar parts is only O(mn). In addition to this improvement in efficiency, we also obtain comparable accurate matching with fewer shape descriptors. Also, in contrast to arbitrary distance functions that are used by previous methods, we use a probabilistic similarity measurement, p-value, to evaluate the similarity of two shapes. Our experiments on several public shape databases indicate that our method outperforms state-of-the-art global and partial shape matching algorithms in various scenarios.
CITATION
Longbin Chen, Rogerio Feris, Matthew Turk, "Efficient partial shape matching using Smith-Waterman algorithm", CVPRW, 2008, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops 2008, pp. 1-6, doi:10.1109/CVPRW.2008.4563078
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