Contourlet-based Manifold Learning for Face Recognition

	Contourlet-based Manifold Learning for Face Recognition
	Zhao, Zhenhua; Hao, Xiaohong
	2012
关键词	Contourlet domain manifold learning Locality preserving projection Gabor transform
页码	196-199
英文摘要	A novel algorithm based on the hybrid of contourlet and manifold learning is proposed for face recognition. In this study, the features of the low frequency and directional subbands in contoulet domain are first extracted, with the low frequency components sensitive to illumination variations ignored to effectively alleviate the effect of illuminations. Then the dimensionality of features is reduced by using manifold learning. Finally the face image is recognized via the nearest neighbourhood classifier. Experimental results on the Yale Face database B and PIE show significant performance improvement of our method compared with other existing methods.
会议录	2012 2ND INTERNATIONAL CONFERENCE ON UNCERTAINTY REASONING AND KNOWLEDGE ENGINEERING (URKE)
会议录出版者	IEEE
会议录出版地	345 E 47TH ST, NEW YORK, NY 10017 USA
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS记录号	WOS:000310348600046
内容类型	会议论文
源URL	[http://119.78.100.223/handle/2XXMBERH/37208]
专题	电气工程与信息工程学院
通讯作者	Zhao, Zhenhua
作者单位	Lanzhou Univ Technol, Coll Elect & Informat Engn, Lanzhou, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Zhenhua,Hao, Xiaohong. Contourlet-based Manifold Learning for Face Recognition[C]. 见:.