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Kernel Canonical Correlation with Similarity Refinement for Automatic Image Tagging
2010
2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Automatic image tagging (AIT) is an effective technology to facilitate the process of image retrieval without requiring user to provide a retrieval instance beforehand. In this paper, we propose an AIT method based on kernel canonical correlation analysis (KCCA) with similarity refinement (KCCSR). As a statistic correlation technique, the KCCA aims at extracting some kind of hidden information shared commonly by the two random variables. Different from the previous KCCA based tagging methods,
doi:10.1109/iihmsp.2010.145
dblp:conf/iih-msp/XiaoZZ10
fatcat:wjeqhvow7nh63lpwnaze5obokm