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 Article
Fast algorithms for mining association rules
TL;DR: Two new algorithms for solving thii problem that are fundamentally different from the known algorithms are presented and empirical evaluation shows that these algorithms outperform theknown algorithms by factors ranging from three for small problems to more than an order of magnitude for large problems.
Proceedings ArticleDOI
Rank aggregation methods for the Web
TL;DR: A set of techniques for the rank aggregation problem is developed and compared to that of well-known methods, to design rank aggregation techniques that can be used to combat spam in Web searches.
Proceedings ArticleDOI
Attribute and simile classifiers for face verification
TL;DR: Two novel methods for face verification using binary classifiers trained to recognize the presence or absence of describable aspects of visual appearance and a new data set of real-world images of public figures acquired from the internet.
Proceedings ArticleDOI
Context-based vision system for place and object recognition
TL;DR: A low-dimensional global image representation is presented that provides relevant information for place recognition and categorization, and it is shown how such contextual information introduces strong priors that simplify object recognition.
Proceedings ArticleDOI
Understanding images of groups of people
Andrew C. Gallagher,Tsuhan Chen +1 more
TL;DR: This paper introduced contextual features that encapsulate the group structure locally (for each person in the group), and globally (the overall structure of the group) to accomplish a variety of tasks, such as demographic recognition, calculating scene and camera parameters, and even event recognition.