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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
会议名称IEEE International Conference on Multimedia and Expo
会议录名称ICME 2011
会议日期11-15 July 2011
会议地点Barcelona, Spain
摘要This 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.
关键词Kernel-based Multifactor Analysis Near-infared Visual Light Synthesis Quotient Image
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/13284
专题类脑智能研究中心
通讯作者Zhaoxiang Zhang
推荐引用方式
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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