Abstract
This paper presents the image retrieval technique and the analysis of different runs of ImageCLEF 2007 submitted by the CINDI group. An interactive fusion-based search technique is investigated in both context and content-based feature spaces. For a context-based image search, keywords from associated annotation files are extracted and indexed based on the vector space model of information retrieval. For a content-based image search, various global and region-specific local image features are extracted to represent images at different levels of abstraction. Based on a user’s relevance feedback information, multiple textual and visual query refinements are performed and weights are adjusted dynamically in a similarity fusion scheme. Finally, top ranked images are obtained by performing both sequential and simultaneous search processes in the multi-modal (context and content) feature space.
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Rahman, M.M., Desai, B.C., Bhattacharya, P. (2008). An Interactive and Dynamic Fusion-Based Image Retrieval Approach by CINDI. In: Peters, C., et al. Advances in Multilingual and Multimodal Information Retrieval. CLEF 2007. Lecture Notes in Computer Science, vol 5152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85760-0_84
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DOI: https://doi.org/10.1007/978-3-540-85760-0_84
Publisher Name: Springer, Berlin, Heidelberg
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