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

Socpus ID

84906788178 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84906788178

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