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	Maximizing intra-individual correlations for face recognition across pose differences
	Li, Annan ; Shan, Shiguang ; Chen, Xilin ; Gao, Wen
	2009
英文摘要	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. ? 2009 IEEE.; EI; 0
语种	英语
DOI标识	10.1109/CVPRW.2009.5206659
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/263207]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Li, Annan,Shan, Shiguang,Chen, Xilin,et al. Maximizing intra-individual correlations for face recognition across pose differences. 2009-01-01.

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