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GBRPR
2007
Springer

Constellations and the Unsupervised Learning of Graphs

9 years 1 months ago
Constellations and the Unsupervised Learning of Graphs
Abstract. In this paper, we propose a novel method for the unsupervised clustering of graphs in the context of the constellation approach to object recognition. Such method is an EM central clustering algorithm which builds prototypical graphs on the basis of fast matching with graph transformations. Our experiments, both with random graphs and in realistic situations (visual localization), show that our prototypes improve the set median graphs and also the prototypes derived from our previous incremental method. We also discuss how the method scales with a growing number of images.
Boyan Bonev, Francisco Escolano, Miguel Angel Loza
Added 16 Aug 2010
Updated 16 Aug 2010
Type Conference
Year 2007
Where GBRPR
Authors Boyan Bonev, Francisco Escolano, Miguel Angel Lozano, Pablo Suau, Miguel Cazorla, Wendy Aguilar
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