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2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Autotagging Facebook: Social network context improves photo annotation
Anchorage, AK, USA
June 23-June 28
ISBN: 978-1-4244-2339-2
Zak Stone, Harvard University, USA
Todd Zickler, Harvard University, USA
Trevor Darrell, UC Berkeley EECS&ICSI, USA
Most personal photos that are shared online are embedded in some form of social network, and these social networks are a potent source of contextual information that can be leveraged for automatic image understanding. In this paper, we investigate the utility of social network context for the task of automatic face recognition in personal photographs. We combine face recognition scores with social context in a conditional random field (CRF) model and apply this model to label faces in photos from the popular online social network Facebook, which is now the top photo-sharing site on the Web with billions of photos in total. We demonstrate that our simple method of enhancing face recognition with social network context substantially increases recognition performance beyond that of a baseline face recognition system.
Citation:
Zak Stone, Todd Zickler, Trevor Darrell, "Autotagging Facebook: Social network context improves photo annotation," cvprw, pp.1-8, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2008
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