DocumentCode :
1780638
Title :
Aiding face recognition with social context association rule based re-ranking
Author :
Bharadwaj, Samarth ; Vatsa, Mayank ; Singh, Rajdeep
Author_Institution :
IIIT-Delhi, New Delhi, India
fYear :
2014
fDate :
Sept. 29 2014-Oct. 2 2014
Firstpage :
1
Lastpage :
8
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 co-occurrence 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 Web site. The results show that association rules extracted from social context can be used to augment face recognition and improve the identification performance.
Keywords :
data mining; face recognition; inference mechanisms; social networking (online); G-album; SN-collection; association rule extraction; association rule mining; face identification performance improvement; face recognition augmentation; familiar face image recognition improvement; large-social transaction repository; multilevel social context inference; person identity; social context association rule based re-ranking; social networking Web site; Abstracts; Context; Face recognition; Lead;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biometrics (IJCB), 2014 IEEE International Joint Conference on
Conference_Location :
Clearwater, FL
Type :
conf
DOI :
10.1109/BTAS.2014.6996266
Filename :
6996266
Link To Document :
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