Abstract
The multi-modal characteristics of Web image make it possible to unify keywords and visual features for image retrieval in Web context. Most of the existing methods about the integration of these two features focus on the interactive relevance feedback technique, which needs the user’s interaction (i.e. a two-step interactive search). In this paper, an approach based on association rule and clustering techniques is proposed to unify keywords and visual features in a different manner, which seamlessly implements the integration within one-step search. The proposed approach considers both Query By Keyword (QBK) mode and Query By Example (QBE) mode and need not the user’s interaction. The experiment results show the proposed approach remarkably improve the retrieval performance compared with the pure search only based on keywords or visual features, and achieve a retrieval performance approximate to the two-step interactive search without requiring the user’s additional interaction.
This paper is supported by China Next Generation Internet (CNGI) project under grant No.CNGI-04-15-7A.
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He, R., Jin, H., Tao, W., Sun, A. (2006). Unifying Keywords and Visual Features Within One-Step Search for Web Image Retrieval. In: Zhuang, Y., Yang, SQ., Rui, Y., He, Q. (eds) Advances in Multimedia Information Processing - PCM 2006. PCM 2006. Lecture Notes in Computer Science, vol 4261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11922162_61
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DOI: https://doi.org/10.1007/11922162_61
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