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Social relationship discovery and face annotation in personal photo collection

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4 Author(s)
Wing W. Y. Ng ; Machine Learning and Cybernetics Research Lab., School of Computer Science and Engineering, South China University of Technology, Guangzhou, China 510006 ; Tian-Ming Zheng ; Patrick P. K. Chan ; Daniel S. Yeung

As wider use of digital camera in these decades, photograph data from individuals increases dramatically. Many photos with different people are available on the Internet. It stimulates a strong demand on automatic face annotation. Moreover, it becomes more possible to discover potential social information from increasingly large photo collections. Every photo in a photo collection is not isolated. Instead, they are highly related as a whole to represent an event, such as a wedding. In a particular event, people would appear as a group following some rules, like families show up in a wedding and colleagues from the same research group in a conference. We also found that clues of closeness between people imply in photos as well. This paper explores social community from personal photo collection with modularity and proposes a method combining ensemble RBFNN with pairwise social relationship as context for recognizing people. Experiments on a conference photo album shows that a certain embedded social network with community structure is revealed. Our simple approach of face recognition with social context enhances the annotation performance when compared with the baseline method.

Published in:

Machine Learning and Cybernetics (ICMLC), 2011 International Conference on  (Volume:2 )

Date of Conference:

10-13 July 2011