Abstract
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.
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References
Arthur, D., Vassilvitskii, S.: k-means++: The advantages of careful seeding. In: SODA 2007, pp. 1027–1035 (2007)
Aslam, J.A., Montague, M.: Models for metasearch. In: ACM SIGIR (2001)
Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Surf: Speeded up robust features. Computer Vision and Image Understanding 110, 346–359 (2008)
Deselaers, T., Keysers, D., Ney, H.: Features for image retrieval: An experimental comparison. Information Retrieval 11(2), 77–107 (2008)
Duygulu, P., Barnard, K., de Freitas, J.F.G., Forsyth, D. A.: Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part IV. LNCS, vol. 2353, pp. 97–112. Springer, Heidelberg (2002)
Fei-Fei, L., Fergus, R., Perona, P.: Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories. In: CVPR 2004 (2004)
Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient graph-based image segmentation. International Journal of Computer Vision 59, 167–181 (2004)
Flickner, M., Sawhney, H., Niblack, W., et al.: Query by image and video content: the qbic system. IEEE Computer 28(9), 23–32 (1995)
Fox, E.A., Shaw, J.A.: Combination of multiple searches. In: Third Text Retrieval Conference, TREC 1994 (1994)
Gokalp, D., Aksoy, S.: Scene classification using bag-of-regions representations. In: CVPR 2007, pp. 1–8 (2007)
Hofmann, T.: Learning the similarity of documents: an information-geometric approach to document retrieval and categorization. In: Advances in Neural Information Processing Systems (2000)
Ladicky, L., Russel, C., Kohliwu, P.: Associative hierarchical crfs for object class image segmentation. In: ICCV 2009 (2009)
Lee, J.H.: Analyses of multiple evidence combination. In: ACM SIGIR 1997 (1997)
Levinshtein, A., Stere, A., Kutulakos, K.N., Fleet, D.J., Dickinson, S.J., Siddiqi, K.: Turbopixels: Fast superpixels using geometric flows. IEEE PAMI 31, 1–9 (2009)
Li, J., Wang, J.Z.: Automatic linguistic indexing of pictures by a statistical modeling approach. IEEE PAMI 25, 1075–1088 (2003)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 2(60), 91–110 (2004)
Lughofer, E.: Extensions of vector quantization for incremental clustering. Pattern Recognition 41, 995–1011 (2008)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE PAMI 27, 1615–1630 (2005)
Nister, D., Stewenius, H.: Scalable recognition witha vocabulary tree. In: CVPR 2006 (2006)
Ojala, T., Pietikainen, M., Maenpaa, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE PAMI 24, 971–987 (2002)
Rahmani, R., Goldman, S.A., Zhang, H., Cholleti, S.R., Fritts, J.E.: Localized content based image retrieval. IEEE PAMI 30, 1902–1912 (2008)
Ramanathan, V., Mishra, S.S., Mitra, P.: Quadtree decomposition based extended vector space model for image retrieval. In: IEEE WACV (2011)
Sivic, J., Zisserman, A.: Video google: a text retrieval approach to object matching in videos. In: ICCV 2003, vol. 2, pp. 1470–1477 (2003)
Smeulders, A.W.M., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-based image retrieval at the end of the early years. IEEE PAMI 22(12), 1349–1380 (2000)
Souvannavong, F., Merialdo, B., Huer, B.: Region-based video content indexing and retrieval. In: CBMI 2005 (2005)
Tighe, J., Lazebnik, S.: SuperParsing: Scalable Nonparametric Image Parsing with Superpixels. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part V. LNCS, vol. 6315, pp. 352–365. Springer, Heidelberg (2010)
Vieux, R., Benois-Pineau, J., Domenger, J.-P., Braquelaire, A.: Segmentation-based multi-class semantic object detection. Multimedia Tools and Applications, 1–22 (October 2010)
Yeh, T., Lee, J., Darrell, T.: Adaptive vocabulary forests br dynamic indexing and category learning. In: ICCV 2007, pp. 1–8 (October 2007)
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Vieux, R., Benois-Pineau, J., Domenger, JP. (2012). Content Based Image Retrieval Using Bag-Of-Regions. In: Schoeffmann, K., Merialdo, B., Hauptmann, A.G., Ngo, CW., Andreopoulos, Y., Breiteneder, C. (eds) Advances in Multimedia Modeling. MMM 2012. Lecture Notes in Computer Science, vol 7131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27355-1_47
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DOI: https://doi.org/10.1007/978-3-642-27355-1_47
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