Abstract
The paper evaluates an alternative approach to BoW-based image retrieval in large databases. The major improvements are in the re-ranking step (verification of candidates returned by BoW). We propose a novel keypoint description which allows the verification based only on individual keypoint matching (no spatial consistency over groups of matched keypoints is tested). Standard Harris-Affine and Hessian-Affine keypoint detectors with SIFT descriptor are used. The proposed description assigns to each keypoint several words representing photometry and geometry of the keypoint in the context of neighbouring image fragments. The words are Cartesian products of typical SIFT-based words so that huge vocabularies can be built. The preliminary experiments on several popular datasets show significant improvements in the pre-retrieval phase combined with a dramatically lower complexity of the re-ranking process. Because of that, the proposed methodology is particularly recommended for the retrieval in very large datasets.
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References
Csurka, G., Bray, C., Dance, C., Fan, L., Wilamowski, J.: Visual categorization with bags of keypoints. In: Proceedings of the ECCV 2004, Workshop on Statistical Learning in Computer Vision, Prague, pp. 1–22 (2004)
Chum, O., Perdoch, M., Matas, J.: Geometric min-hashing: Finding a (thick) needle in a haystack. In: Proceedings of the IEEE Conference on CVPR 2009, pp. 17–24 (2009)
Jegou, H., Douze, M., Schmid, C.: Improving bag-of-features for large scale image search. Int. J. Comput. Vis. 87, 316–336 (2010)
Tolias, M., Jegou, H.: Visual query expansion with or without geometry: refining local descriptors by feature aggregation. Pattern Recogn. 47, 3466–3476 (2014)
Ĺšluzek, A.: Visual categorization with bags of contextual descriptors improving credibility of keypoint matching. In: Proceedings of ICARCV 2014, Singapore (2014) (in print)
Zhao, W.L., Ngo, C.W., Tan, H.K., Wu, X.: Near-duplicate keyframe identification with interest point matching and pattern learning. IEEE Trans. Multimedia 9, 1037–1048 (2007)
Mikolajczyk, K., Schmid, C.: Scale and affine invariant interest point detectors. Int. J. Comput. Vis. 60, 63–86 (2004)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60, 91–110 (2004)
Arandjelovic, R., Zisserman, A.: Three things everyone should know to improve object retrieval. In: Proceedings of the IEEE Conference on CVPR 2012, pp. 2911–2918 (2012)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. PAMI 27, 1615–1630 (2005)
Nistér, D., Stewénius, H.: Scalable recognition with a vocabulary tree. In: Proceedings of the IEEE Conference on CVPR 2006, vol. 2, pp. 2161–2168 (2006)
Stewénius, H., Gunderson, S.H., Pilet, J.: Size matters: exhaustive geometric verification for image retrieval Accepted for ECCV 2012. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part II. LNCS, vol. 7573, pp. 674–687. Springer, Heidelberg (2012)
Zhang, Y., Jia, Z., Chen, T.: Image retrieval with geometry-preserving visual phrases. In: Proceedings of the IEEE Conference CVPR 2011, pp. 809–816 (2011)
Sivic, J., Zisserman, A.: Video google: a text retrieval approach to object matching in videos. In: Proceedings of 9th IEEE Conference on ICCV 2003, Nice, vol. 2, pp. 1470–1477 (2003)
Cha, S.H., Srihari, S.: On measuring the distance between histograms. Pattern Recogn. 35, 1355–1370 (2002)
Swain, M., Ballard, D.: Color indexing. Int. J. Comput. Vis. 7, 11–32 (1991)
Philbin, J., Chum, O., Isard, M., Sivic, J., Zisserman, A.: Object retrieval with large vocabularies and fast spatial matching. In: Proceedings of the IEEE Conference on CVPR 2007, pp. 1–8 (2007)
Paradowski, M., Śluzek, A.: Local keypoints and global affine geometry: triangles and ellipses for image fragment matching. In: Kwaśnicka, H., Jain, L.C. (eds.) Innovations in Intelligent Image Analysis. SCI, vol. 339, pp. 195–224. Springer, Heidelberg (2011)
Śluzek, A., Paradowski, M.: Visual similarity issues in face recognition. Int. J. Biometrics 4, 22–37 (2012)
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Ĺšluzek, A. (2015). Extended Keypoint Description and the Corresponding Improvements in Image Retrieval. In: Jawahar, C., Shan, S. (eds) Computer Vision - ACCV 2014 Workshops. ACCV 2014. Lecture Notes in Computer Science(), vol 9008. Springer, Cham. https://doi.org/10.1007/978-3-319-16628-5_50
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DOI: https://doi.org/10.1007/978-3-319-16628-5_50
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