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Bag-of-words model is one of the most widely used methods in the recent studies of multimedia data retrieval. The key idea of the bag-of-words model is to quantize the bag of local features, for example SIFT, to a histogram of visual words and then standard information retrieval technologies developed from text retrieval can be applied directly. Despite its success, one problem of the bag-of-words...
The continued explosion in the growth of image and video databases makes automatic image search and retrieval an extremely important problem. Among the various approaches to Content-based Image Retrieval (CBIR), image similarity based on local point descriptors has shown promising performance. However, this approach suffers from the scalability problem. Although bag-of-words model resolves the scalability...
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