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Discovering shape classes using tree edit-distance and pairwise clustering

Torsello, Andreas; Robles-Kelly, Antonio; Hancock, Edwin R


This paper describes work aimed at the unsupervised learning of shape-classes from shock trees. We commence by considering how to compute the edit distance between weighted trees. We show how to transform the tree edit distance problem into a series of maximum weight clique problems, and show how to use relaxation labeling to find an approximate solution. This allows us to compute a set of pairwise distances between graph-structures. We show how the edit distances can be used to compute a...[Show more]

CollectionsANU Research Publications
Date published: 2007
Type: Journal article
Source: International Journal of Computer Vision
DOI: 10.1007/s11263-006-8929-y


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