A hybrid-supervision learning algorithm for real-time un-completed face recognition

doi:10.1016/j.compeleceng.2022.108090

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 视频内容安全

	A hybrid-supervision learning algorithm for real-time un-completed face recognition
	Zhao, Shuhuan 1,2; Liu, Wen 1,2; Liu, Shuaiqi 1,2,3; Ge, Jiaqi 1,2; Liang, Xiaolin 1,2
发表期刊	COMPUTERS & ELECTRICAL ENGINEERING
ISSN	0045-7906
	2022-07-01
卷号	101 页码:17
通讯作者	Liu, Shuaiqi(shdkj_l918@163.com)
摘要	It is still an important and challenging problem for face recognition with occlusion, small sample size, various expressions, and poses, called un-completed face recognition. So we design a simple but effective hybrid-supervision learning frame by fusing the advantages of supervised and unsupervised features. In the supervised branch, we propose an effective feature learning method: HMMFA. In the unsupervised branch, we improve the PCANet to extract more effective local information. In the fusion stage, we further extract the discriminant features contained in the hybrid features and then take SVM as the final classifier. Because the proposed method requires no auxiliary set and has less parameter number than that of deep learning methods, it has a low storage requirement, which makes it more economical and practical for small communities. Experiments on four databases show the effectiveness and efficiency of our method.
关键词	Face recognition Feature fusion Hybrid supervised learning Multiple marginal Fisher analysis
DOI	10.1016/j.compeleceng.2022.108090
关键词[WOS]	REGRESSION
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[62172139] ; Natural Science Foundation of Hebei Province[F2020201025] ; Natural Science Foundation of Hebei Province[F2019201151] ; Natural Science Foundation of Hebei Province[F2019201362] ; Natural Science Foundation of Hebei Province[F2018210148] ; Science Research Project of Hebei Province[BJ2020030] ; Science Research Project of Hebei Province[QN2017306] ; Open Project Program of NLPR[202200007] ; Foundation of President of Hebei University[XZJJ201909] ; High-Performance Computing Center of Hebei University
项目资助者	National Natural Science Foundation of China ; Natural Science Foundation of Hebei Province ; Science Research Project of Hebei Province ; Open Project Program of NLPR ; Foundation of President of Hebei University ; High-Performance Computing Center of Hebei University
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Interdisciplinary Applications ; Engineering, Electrical & Electronic
WOS记录号	WOS:000849743000011
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：9[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/50024
专题	多模态人工智能系统全国重点实验室_视频内容安全
通讯作者	Liu, Shuaiqi
作者单位	1.Hebei Univ, Coll Elect & Informat Engn, Baoding 071002, Peoples R China 2.Machine Vis Technol Innovat Ctr Hebei, Baoding 071002, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit NLPR, Beijing 100190, Peoples R China
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Zhao, Shuhuan,Liu, Wen,Liu, Shuaiqi,et al. A hybrid-supervision learning algorithm for real-time un-completed face recognition[J]. COMPUTERS & ELECTRICAL ENGINEERING,2022,101:17.
APA	Zhao, Shuhuan,Liu, Wen,Liu, Shuaiqi,Ge, Jiaqi,&Liang, Xiaolin.(2022).A hybrid-supervision learning algorithm for real-time un-completed face recognition.COMPUTERS & ELECTRICAL ENGINEERING,101,17.
MLA	Zhao, Shuhuan,et al."A hybrid-supervision learning algorithm for real-time un-completed face recognition".COMPUTERS & ELECTRICAL ENGINEERING 101(2022):17.