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	Design sparse features for age estimation using hierarchical face model
	Suo, Jinli ; Wu, Tianfu ; Zhu, Songchun ; Shan, Shiguang ; Chen, Xilin ; Gao, Wen
	2008
英文摘要	A key point in automatic age estimation is to design feature set essential to age perception. To achieve this goal, this paper builds up a hierarchical graphical face model for faces appearing at low, middle and high resolution respectively. Along the hierarchy, a face image is decomposed into detailed parts from coarse to fine. Then four types of features are extracted from this graph representation guided by the priors of aging process embedded in the graphical model: topology, geometry, photometry and configuration. On age estimation, this paper follows the popular regression formulation for mapping feature vectors to its age label. The effectiveness of the presented feature set is justified by testing results on two datasets using different kinds of regression methods. The experimental results in this paper show that designing feature set for age estimation under the guidance of hierarchical face model is a promising method and a flexible framework as well. ? 2008 IEEE.; EI; 0
语种	英语
DOI标识	10.1109/AFGR.2008.4813314
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/263257]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Suo, Jinli,Wu, Tianfu,Zhu, Songchun,et al. Design sparse features for age estimation using hierarchical face model. 2008-01-01.

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