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	Lighting aware preprocessing for face recognition across varying illumination
	Han, Hu ; Shan, Shiguang ; Qing, Laiyun ; Chen, Xilin ; Gao, Wen
	2010
英文摘要	Illumination variation is one of intractable yet crucial problems in face recognition and many lighting normalization approaches have been proposed in the past decades. Nevertheless, most of them preprocess all the face images in the same way thus without considering the specific lighting in each face image. In this paper, we propose a lighting aware preprocessing (LAP) method, which performs adaptive preprocessing for each testing image according to its lighting attribute. Specifically, the lighting attribute of a testing face image is first estimated by using spherical harmonic model. Then, a von Mises-Fisher (vMF) distribution learnt from a training set is exploited to model the probability that the estimated lighting belongs to normal lighting. Based on this probability, adaptive preprocessing is performed to normalize the lighting variation in the input image. Extensive experiments on Extended YaleB and Multi-PIE face databases show the effectiveness of our proposed method. ? 2010 Springer-Verlag.; EI; 0
语种	英语
DOI标识	10.1007/978-3-642-15552-9_23
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/329823]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Han, Hu,Shan, Shiguang,Qing, Laiyun,et al. Lighting aware preprocessing for face recognition across varying illumination. 2010-01-01.

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