Smart batch tagging of photo albums

As one of the emerging Web 2.0 activities, tagging becomes a popular approach to manage personal media data, such as photo albums. However, exhaustively tagging all photos in an album is a labor-intensive and time-consuming task, and simply entering tags for the whole album will significantly degrade the tagging accuracy. In this paper, we propose a smart batch tagging scheme that aims at facilitating users in album tagging. For a given album, it selects a set of representative exemplars for manual tagging, where the number of exemplars is dependent on the content of the photos.Then the tags of the rest photos are automatically inferred.In this way, the number of tagged photos is significantly reduced and we will show that high tagging accuracy can still be maintained. Therefore, a good trade-off between manual efforts and tagging performance can be achieved. Experimental results have demonstrated the effectiveness and usefulness of the proposed approach.

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