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SemView: A Semantic-sensitive Distributed Image Retrieval System

State-of-the-art image retrieval techniques have been developed to support high-level (semantics) querying and browsing of images. For certain user queries, it is also very important to know about the information about the remote image databases on the Internet so that the queries can be guided toward the most relevant databases. In this paper, we introduce a novel system, Sem View, which supports both visual and semantic queries and intelligently ranks the distributed image databases for the queries. Our system summarizes the visual and semantic contents of each database in a metadatabase, which is a collection of automatically generated visual, semantic and statistical metadata. With the metadatabase, our system can effectively guide the user queries toward the most relevant image databases in a distributed environment for better retrieval performance.