We address the problem of automated face recognition on a social network using a loopy belief propagation frame- work. The proposed approach propagates the identities of faces in photos across social graphs. We characterize performance in terms of structural properties of a social network. We propose a distance metric defined using face recognition results for detecting hidden connections. The result demonstrates that the constraints imposed by the social network have the potential to improve the performance of face recognition methods. The result also shows it is possible to discover hidden connections in a social network based on face recognition.
Conference Dates: September 30-October 2, 2013
Conference Location: Arlington, VA
Conference Title: The IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS 2013)
Pub Type: Conferences