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In this paper, we propose a novel approach to address the problem of the huge amount of local features for a large-scale database. First, in each image the local features are organized into dozens of groups by performing the standard -means clustering algorithm on their spatial positions. Second, a compact descriptor is generated to describe the visual information of each group of local features...
Recently, Bag-of-Words(BoW) model has been widely used for feature representation in multimedia search area due to its simplification and effectiveness. While various variants of BoW models have been developed to improve the discriminative cabability, less efforts have been paid on discovering the working mechanism underlying them. In this paper, we systematically investigate the impact of various...
One of the main limitations of image search based on bag-of-features is the memory usage per image. Only a few million images can be handled on a single machine in reasonable response time. In this paper, we first evaluate how the memory usage is reduced by using lossless index compression. We then propose an approximate representation of bag-of-features obtained by projecting the corresponding histogram...
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