Abstract
In this article we address the problem of searching for products using an image as query, instead of the more popular approach of searching by textual keywords. With the fast development of the Internet, the popularization of mobile devices and e-commerce systems, searching specific products by image has become an interesting research topic. In this context, Content-Based Image Retrieval (CBIR) techniques have been used to support and enhance the customer shopping experience. We propose an image re-ranking strategy based on multimedia information available on product databases. Our re-ranking strategy relies on category and textual information associated to the top-k images of an initial ranking computed purely with CBIR techniques. Experiments were carried out with users’ relevance judgment on two image datasets collected from e-commerce Web sites. Our results show that our re-ranking strategy outperforms the baselines when using only CBIR techniques.
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References
Arampatzis, A., Zagoris, K., Chatzichristofis, S.A.: Dynamic Two-Stage Image Retrieval from Large Multimodal Databases. In: Clough, P., Foley, C., Gurrin, C., Jones, G.J.F., Kraaij, W., Lee, H., Mudoch, V. (eds.) ECIR 2011. LNCS, vol. 6611, pp. 326–337. Springer, Heidelberg (2011)
Chandrasekhar, V.R., Chen, D.M., Tsai, S.S., Cheung, N.M., Chen, H., Takacs, G., Reznik, Y., Vedantham, R., Grzeszczuk, R., Bach, J., Girod, B.: The stanford mobile visual search data set. In: MMSys, pp. 117–122 (2011)
Chang, S., Sikora, T., Purl, A.: Overview of the mpeg-7 standard. IEEE Transactions on Circuits and Systems for Video Technology 11(6), 688–695 (2001)
Chatzichristofis, S.A., Boutalis, Y.S.: CEDD: Color and Edge Directivity Descriptor: A Compact Descriptor for Image Indexing and Retrieval. In: Gasteratos, A., Vincze, M., Tsotsos, J.K. (eds.) ICVS 2008. LNCS, vol. 5008, pp. 312–322. Springer, Heidelberg (2008)
Chatzichristofis, S., Boutalis, Y.: Fcth: Fuzzy color and texture histogram - a low level feature for accurate image retrieval. In: WIAMIS, pp. 191–196 (2008)
Chen, Y., Yu, N., Luo, B., Chen, X.: ilike: integrating visual and textual features for vertical search. In: ACM MM, pp. 221–230 (2010)
Hou, A., Liu-Qing, Z., Dong-Cheng, S.: Garment image retrieval based on multi-features. In: IEEE CMCE, vol. 6, pp. 194–197 (2010)
Huang, J., Kumar, S., Mitra, M., Zhu, W., Zabih, R.: Image indexing using color correlograms. In: IEEE CVPR, pp. 762–768 (1997)
Jain, V., Varma, M.: Learning to re-rank: query-dependent image re-ranking using click data. In: ACM WWW, pp. 277–286 (2011)
Kejia, W., Honggang, Z., Lunshao, C., Ping, Z., et al.: A comparative study of moment-based shape descriptors for product image retrieval. In: IASP, pp. 355–359 (2011)
Kimura, P., Cavalcanti, J., Saraiva, P., Torres, R., Gonçalves, M.: Evaluating retrieval effectiveness of descriptors for searching in large image databases. JIDM 2(3), 305–321 (2011)
Lin, X., Gokturk, B., Sumengen, B., Vu, D.: Visual search engine for product images. In: Proc. SPIE 6820, Multimedia Content Access: Algorithms and Systems II, pp. 1–9 (2008)
Liu, Y., Mei, T., Hua, X.: Crowdreranking: exploring multiple search engines for visual search reranking. In: ACM SIGIR, pp. 500–507 (2009)
Lux, M.: Content based image retrieval with lire. In: ACM MM, pp. 735–738 (2011)
McGill, M., Salton, G.: Introduction to Modern Information Retrieval. McGraw-Hill (1983)
Pedronette, D., Torres, R.: Exploiting contextual spaces for image re-ranking and rank aggregation. In: ACM ICMR, pp. 1–8 (2011)
Penatti, O., da Silva Torres, R.: Color descriptors for web image retrieval: a comparative study. In: SIBGRAPI, pp. 163–170 (2008)
Popescu, A., Moëllic, P., Kanellos, I., Landais, R.: Lightweight web image reranking. In: ACM MM, pp. 657–660 (2009)
Stehling, R., Nascimento, M., Falcão, A.: A compact and efficient image retrieval approach based on border/interior pixel classification. In: ACM CIKM, pp. 102–109 (2002)
Tseng, C., Hung, S., Tsay, J.: An efficient garment visual search based on shape context. In: WSEAS MUSP, pp. 223–230 (2009)
Xie, X., Lu, L., Jia, M., Li, H., Seide, F., Ma, W.Y.: Mobile search with multimodal queries. Proceedings of the IEEE, 589–601 (2008)
Yao, T., Mei, T., Ngo, C.: Co-reranking by mutual reinforcement for image search. In: ACM CIVR, pp. 34–41 (2010)
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dos Santos, J.M., Cavalcanti, J.M.B., Saraiva, P.C., de Moura, E.S. (2013). Multimodal Re-ranking of Product Image Search Results. In: Serdyukov, P., et al. Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36973-5_6
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DOI: https://doi.org/10.1007/978-3-642-36973-5_6
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