Cross-pose face recognition based on partial least squares

摘要

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.