Title
Exploring Album Structure For Face Recognition In Online Social Networks
Keywords
Face recognition; Online social networks; Structural SVM
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. © 2014 Elsevier B.V. All rights reserved.
Publication Date
1-1-2014
Publication Title
Image and Vision Computing
Volume
32
Issue
10
Number of Pages
751-760
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1016/j.imavis.2014.01.002
Copyright Status
Unknown
Socpus ID
84906788178 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84906788178
STARS Citation
Hochreiter, Jason; Han, Zhongkai; Masood, Syed Zain; Fonte, Spencer; and Tappen, Marshall, "Exploring Album Structure For Face Recognition In Online Social Networks" (2014). Scopus Export 2010-2014. 9402.
https://stars.library.ucf.edu/scopus2010/9402