Proceedings ArticleDOI
Aiding face recognition with social context association rule based re-ranking
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TLDR
The results show that association rules extracted from social context can be used to augment face recognition and improve the identification performance.Abstract:
Humans are very efficient at recognizing familiar face images even in challenging conditions. One reason for such capabilities is the ability to understand social context between individuals. Sometimes the identity of the person in a photo can be inferred based on the identity of other persons in the same photo, when some social context between them is known. This research presents an algorithm to utilize cooccurrence of individuals as the social context to improve face recognition. Association rule mining is utilized to infer multi-level social context among subjects from a large repository of social transactions. The results are demonstrated on the G-album and on the SN-collection pertaining to 4675 identities prepared by the authors from a social networking website. The results show that association rules extracted from social context can be used to augment face recognition and improve the identification performance.read more
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References
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Proceedings ArticleDOI
Evaluation of face recognition techniques for application to facebook
Brian C. Becker,Enrique G. Ortiz +1 more
TL;DR: A method to automatically gather and extract face images from Facebook, resulting in over 60,000 faces datasets is presented, and a variety of well-known face recognition algorithms are evaluated against holistic performance metrics of accuracy, speed, memory usage, and storage size.
Book ChapterDOI
Joint people, event, and location recognition in personal photo collections using cross-domain context
TL;DR: This work develops a unified approach to jointly tag across multiple domains (specifically people, events, and locations) using a generic probabilistic model of context that couples the domains through a set of cross-domain relations.
Proceedings ArticleDOI
Using Group Prior to Identify People in Consumer Images
Andrew C. Gallagher,Tsuhan Chen +1 more
TL;DR: By modeling the relationships between the people with the group prior, this paper improves classification performance and shows that despite errors in resolving ambiguous labels, useful classifiers can be trained with the resolved labels.
Proceedings ArticleDOI
Which faces to tag: Adding prior constraints into active learning
TL;DR: An algorithm is introduced that guides the user to tag faces in the best possible order during a face recognition assisted tagging scenario using a probabilistic discriminative model that models the posterior distributions by propagating label information using a message passing scheme.
Proceedings ArticleDOI
Discovering informative social subgraphs and predicting pairwise relationships from group photos
TL;DR: A novel framework to connect faces of different attributes and positions as a face graph and discover informative subgraphs to represent social subgroups in group photos is proposed and significantly outperform prior work which considers merely facial attributes for determining pairwise relationships.