Sciweavers

Share
CVPR
2009
IEEE

Maximizing Intra-individual Correlations for Face Recognition Across Pose Differences

13 years 3 months ago
Maximizing Intra-individual Correlations for Face Recognition Across Pose Differences
The variations of pose lead to significant performance decline in face recognition systems, which is a bottleneck in face recognition. A key problem is how to measure the similarity between two image vectors of unequal length that viewed from different pose. In this paper, we propose a novel approach for pose robust face recognition, in which the similarity is measured by correlations in a media subspace between different poses on patch level. The media subspace is constructed by Canonical Correlation Analysis, such that the intra-individual correlations are maximized. Based on the media subspace two recognition approaches are developed. In the first, we transform non-frontal face into frontal for recognition. And in the second, we perform recognition in the media subspace with probabilistic modeling. The experimental results on FERET database demonstrate the efficiency of our approach.
Annan Li (Chinese Academy of Sciences), Shiguang S
Added 09 May 2009
Updated 10 Dec 2009
Type Conference
Year 2009
Where CVPR
Authors Annan Li (Chinese Academy of Sciences), Shiguang Shan (Chinese Academy of Sciences), Xilin Chen (Chinese Academy of Sciences), Wen Gao (Chinese Academy of Sciences)
Comments (0)
books