| Web-Data Driven Approach for Bridging the Gap between Image Content and Concept (2008) | |||||||||||||||
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| Abstract. Due to the semantic gap, current content-based image retrieval framework can not satisfy the complex demands created by a user’s preferences and subjectivity. To retrieve images in a concept-level becomes an urgent need. However, a key challenge of such applications is to get enough training data to learn the mapping functions from low-level feature spaces to high-level semantics. In this paper, we propose to use Web images as training data and Web link structure as manifold learning clues to automatically convert image visual descriptors to semantic concepts. An image thesaurus is constructed by first extracting the right keywords and associating them with the corresponding regions in the images, and then organizing the descriptors according to website link structure. A concept-based image retrieval method which effectively leverages the learned thesaurus is also presented. 1 | |||||||||||||||
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