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We define localized content-based image retrieval as a CBIR task where the user is only interested in a portion of the image, and the rest of the image is irrelevant. In this paper we present a localized CBIR system, ACCIO! , that uses labeled images in conjunction with a multiple-instance learning algorithm to first identify the desired object and weight the features accordingly, and then to rank images in the database using a similarity measure that is based upon only the relevant portions ofdoi:10.1145/1101826.1101863 dblp:conf/mir/RahmaniGZKF05 fatcat:r5n6smyvura47hel75trdecpva