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Cross-pose Face Recognition by Canonical Correlation Analysis
[article]
2015
arXiv
pre-print
The pose problem is one of the bottlenecks in automatic face recognition. We argue that one of the diffculties in this problem is the severe misalignment in face images or feature vectors with different poses. In this paper, we propose that this problem can be statistically solved or at least mitigated by maximizing the intra-subject across-pose correlations via canonical correlation analysis (CCA). In our method, based on the data set with coupled face images of the same identities and across
arXiv:1507.08076v1
fatcat:airjyjndxvgtvlrol7i4hg2kwa