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Most existing image set classification methods use either appearance variations or temporal information to represent semantic knowledge (relationships) and subject appearance. Such methods usually rely on a predetermined surface structures that the image sets could lie on, and/or are highly influenced by the temporal correlations between images within the image sets. In contrast, this paper introduces...
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