Cross-pose face recognition based on partial least squares

Authors:
Annan Li;Shiguang Shan;Xilin Chen;Wen Gao
Affiliations:
Key Lab of Intelligent Information Processing of Chinese Academy of Sciences, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China and Graduate University of Chine ...;Key Lab of Intelligent Information Processing of Chinese Academy of Sciences, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;Key Lab of Intelligent Information Processing of Chinese Academy of Sciences, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;Institute of Digital Media, Peking University, Beijing 100871, China and Key Lab of Intelligent Information Processing of Chinese Academy of Sciences, Institute of Computing Technology, Chinese Ac ...
Venue:
Pattern Recognition Letters
Year:
2011

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Abstract

The pose problem is one of the bottlenecks for face recognition. In this paper we propose a novel cross-pose face recognition method based on partial least squares (PLS). By training on the coupled face images of the same identities and across two different poses, PLS maximizes the squares of the intra-individual correlations. Therefore, it leads to improvements in recognizing faces across pose differences. The experimental results demonstrate the effectiveness of the proposed method.