Image retrieval with graph kernel on regions.
Résumé
In the framework of the interactive search in image databases, we are interested in similarity measures able to learn during the search and usable in real-time. Im- ages are represented by adjacency graphs of fuzzy re- gions. In order to compare attributed graphs, we em- ploy kernels on graphs built on sets of paths. In this pa- per, we introduce a fast kernel function whose similar- ity is based on several matches. We also introduce new features for edges in the graph. Experiments on a spe- cific database having objects with heterogeneous back- grounds show the performance of our object retrieval technique.
Domaines
Machine Learning [stat.ML]
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