Exploring album structure for face recognition in online social networks |
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Authors: | Jason Hochreiter Zhongkai HanSyed Zain Masood Spencer FonteMarshall Tappen |
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Affiliation: | University of Central Florida, 4000 Central Florida Blvd., Orlando, FL 32816, United States |
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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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Keywords: | Face recognition Online social networks Structural SVM |
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