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Face Synthesis From Near-Infrared To Visual Light Spectrum Using Quotient Image And Kernel-Based Multifactor Analysis
Zeda Zhang; Yunhong Wang; Zhaoxiang Zhang; Guangpeng Zhang
2011-07-11
Conference NameIEEE International Conference on Multimedia and Expo
Source PublicationICME 2011
Conference Date11-15 July 2011
Conference PlaceBarcelona, Spain
AbstractThis paper addresses the problem of synthesizing an artificial visual light (VIS) facial image from near-infrared (NIR) input. After extensively assessing photic characteristics of tissues at human skin surface, we propose a framework for this task. Firstly, we take the quotient images for training and reconstruction, so that information related to face structure can be preserved. Secondly, to handle heterogeneous blur resulted from multiple scattering within tissues, we introduce kernel based strategy as a powerful nonlinear analyzing instrument. Finally, as in our application the image ensembles involve multiple factors, a tensor structure is employed to transform heterogeneous face data into uniform subspaces. Comparative results show that our synthesized images are both suited for human vision and discriminative for machine recognition.
KeywordKernel-based Multifactor Analysis Near-infared Visual Light Synthesis Quotient Image
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/13284
Collection类脑智能研究中心
Corresponding AuthorZhaoxiang Zhang
Recommended Citation
GB/T 7714
Zeda Zhang,Yunhong Wang,Zhaoxiang Zhang,et al. Face Synthesis From Near-Infrared To Visual Light Spectrum Using Quotient Image And Kernel-Based Multifactor Analysis[C],2011.
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