Album-oriented face recognition for online social networks
FG(2013)
Abstract
In this paper, we propose an album-oriented face-recognition model that exploits the album structure for face recognition in online social networks. Albums, usually associated with pictures of a small group of people at a certain event or occasion, provide vital information that can be used to effectively reduce the possible list of candidate labels. We show how this intuition can be formalized into a model that expresses a prior on how albums tend to have many pictures of a small number of people. We also show how it can be extended to include other information available in a social network. Using two real-world datasets independently drawn from Facebook, we show that this model is broadly applicable and can significantly improve recognition rates.
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Key words
candidate labels,face recognition,album-oriented face recognition,facebook,online social networks,social networking (online),real-world datasets,labeling,face,vectors
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