VisualRank: Applying PageRank to Large-Scale Image Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual diversification of image search results
Proceedings of the 18th international conference on World wide web
Generic similarity search engine demonstrated by an image retrieval application
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Query aware visual similarity propagation for image search reranking
MM '09 Proceedings of the 17th ACM international conference on Multimedia
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With the rapid growth of multimedia data, a lot of attention has been recently devoted to the development of multimedia retrieval systems. The research has followed two main directions: The first one applies existing text-search mechanisms to retrieve multimedia data based on its descriptive annotations, the second approach retrieves data by content. In case of text-based searching, the quality of results depends on the quality of text metadata, which is often not very high (especially in large general-purpose collections such as web image galleries). In the content-based approach, data objects are indexed and searched using features extracted from the data that describe their important characteristics. However, this solution suffers from the well-known semantic gap problem, i.e. the discrepancy between the similarity as computed using the descriptors and human understanding of similarity.