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	Face hallucination based on neighbor embedding via illumination adaptation
	Song, Sijie ; Li, Yanghao ; Gao, Zhihan ; Liu, Jiaying
	2015
英文摘要	In this paper, we present a novel face hallucination method by neighbor embedding considering illumination adaptation (NEIA) to super-resolve faces when the lighting conditions of the training faces mismatch those of the testing face. For illumination adjustment, face alignment is employed through dense correspondence. Next, every training face is composed into two layers to extract both details and highlight components. By operating the two layers of each face respectively, an extended training set is acquired by combining the original and adapted faces compensated in illumination. Finally, we reconstruct the input faces through neighbor embedding. To improve the estimation of neighbor embedding coefficients, nonlocal similarity is taken into consideration. Experimental results show that the proposed method outperforms other state-of-the-art methods both in subjective and objective qualities. ? 2015 Asia-Pacific Signal and Information Processing Association.; EI; 680-683
语种	英语
出处	2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2015
DOI标识	10.1109/APSIPA.2015.7415357
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/449530]
专题	计算机科学技术研究所
推荐引用方式 GB/T 7714	Song, Sijie,Li, Yanghao,Gao, Zhihan,et al. Face hallucination based on neighbor embedding via illumination adaptation. 2015-01-01.

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