CASIA OpenIR  > 智能制造技术与系统研究中心  > 多维数据分析
An adaptive learning method for face hallucination using locality preserving projections
Zhang Xuesong; Peng Silong; Jiang Jing; Xuesong Zhang
2008
Conference Name2008 8th IEEE International Conference on Automatic Face and Gesture Recognition FG 2008
Conference Date2008/9/17-2008/9/19
Conference PlaceNetherlandsAmsterdam Netherlands
AbstractThe size of training set as well as the usage thereof is an important issue of learning-based super-resolution. In this paper we presented an adaptive learning method for face hallucination using Locality Preserving Projections (LPP). By virtue of the ability to reveal the non-linear structure hidden in the high–dimensional image space LPP is an efficient manifold learning method to analyze the local intrinsic features on the manifold of local facial areas. By searching out patches online in the LPP sub-space which makes the resultant training set tailored to the testing patch our algorithm performed the adaptive sample selection and then effectively restored the lost high-frequency components of the low-resolution face image by patch-based eigentransformation using the dynamic training set. Finally experiments fully demonstrated that the proposed method can achieve good performance of super-resolution reconstruction by utilizing a relative small sample.
Keyword
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12879
Collection智能制造技术与系统研究中心_多维数据分析
Corresponding AuthorXuesong Zhang
Recommended Citation
GB/T 7714
Zhang Xuesong,Peng Silong,Jiang Jing,et al. An adaptive learning method for face hallucination using locality preserving projections[C],2008.
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