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Pattern Recognition, International Conference on (2010)
Istanbul, Turkey
Aug. 23, 2010 to Aug. 26, 2010
ISSN: 1051-4651
ISBN: 978-0-7695-4109-9
pp: 918-921
ABSTRACT
This paper focusses on the problem of locating object class exemplars from a large corpus of images using a infinity propagation. We use attributed relational graphs to represent groups of local invariant features together with their spatial arrangement. Rather than mining exemplars from the entire graph corpus, we prefer to cluster object specific exemplars. Firstly, we obtain an object specific cluster of graphs using similarity propagation. The popular a nity propagation method is then individually applied to each object specific cluster. Using this clustering method, we can obtain object specific exemplars together with a high precision for the data associated with each exemplar. Experiments are performed on over 80K images spanning 500 objects, and demonstrate the performance of the method in terms of efficiency, scalability.
INDEX TERMS
Afinity Propagation, Class Specific Hyper Graph, Mining Exemplars
CITATION

J. Liu, E. Hancock and S. Xia, "Mining Exemplars for Object Modelling Using Affinity Propagation," 2010 20th International Conference on Pattern Recognition (ICPR 2010)(ICPR), Istanbul, 2010, pp. 918-921.
doi:10.1109/ICPR.2010.1149
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