Title
Exploring album structure for face recognition in online social networks
Abbreviated Journal Title
Image Vis. Comput.
Keywords
Face recognition; Online social networks; Structural SVM; Computer Science, Artificial Intelligence; Computer Science, Software; Engineering; Computer Science, Theory & Methods; Engineering, Electrical; & Electronic; Optics
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. (C) 2014 Elsevier B.V. All rights reserved.
Journal Title
Image and Vision Computing
Volume
32
Issue/Number
10
Publication Date
1-1-2014
Document Type
Article
Language
English
First Page
751
Last Page
760
WOS Identifier
ISSN
0262-8856
Recommended Citation
"Exploring album structure for face recognition in online social networks" (2014). Faculty Bibliography 2010s. 5450.
https://stars.library.ucf.edu/facultybib2010/5450
Comments
Authors: contact us about adding a copy of your work at STARS@ucf.edu