In this work we introduce the Bag-Of-Regions model, inspired from the Bag-Of-Visual-Words. Instead of clustering local image patches represented by SIFT or related descriptors, low level descriptors are extracted and clustered from image regions, as given by a segmentation algorithm. The Bag-Of-Region model allows to define visual dictionaries that capture extra information with respect to Bag-Of-Visual-Words. Combined description schemes and ad-hoc incremental clustering for visual dictionnaries are proposed. The results on public datasets are promising. © 2012 Springer-Verlag.
CITATION STYLE
Vieux, R., Benois-Pineau, J., & Domenger, J. P. (2012). Content based image retrieval using bag-of-regions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7131 LNCS, pp. 507–517). https://doi.org/10.1007/978-3-642-27355-1_47
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