Abstract
Automatically naming faces in online social networks enables us to search for photos and build user face models. We consider two common weakly supervised settings where: (1) users are linked to photos, not to faces and (2) photos are not labeled but part of a user's album. The focus is on algorithms that scale up to an entire online social network. We extensively evaluate different graph-based strategies to label faces in both settings and consider dependencies. We achieve results on a par with a recent multi-person approach, but with 60 times less computation time on a set of 300K weakly labeled faces and 1.4 M faces in user albums. A subset of the faces can be labeled with a speed-up of over three orders of magnitude.
Original language | Undefined |
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Pages (from-to) | 2335-2347 |
Number of pages | 13 |
Journal | Pattern recognition |
Volume | 45 |
Issue number | 6 |
DOIs | |
Publication status | Published - Jun 2012 |
Keywords
- HMI-CI: Computational Intelligence
- HMI-MR: MULTIMEDIA RETRIEVAL
- Weak labeling
- Online Social Network
- EWI-21519
- METIS-285135
- IR-79722
- Graph-Based
- Face naming
- Scalability