A novel approach inspired by optic nerve characteristics for few-shot occluded face recognition

doi:10.1016/j.neucom.2019.09.045

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进控制与自动化团队

	A novel approach inspired by optic nerve characteristics for few-shot occluded face recognition
	Zheng, Wenbo 1,3; Gou, Chao 2; Wang, Fei-Yue 3,4
刊名	NEUROCOMPUTING
	2020-02-01
卷号	376 页码:25-41
关键词	Sparse representation Adaptive fusion feature Few-shot learning Face recognition Face occlusion Dictionary learning
ISSN号	0925-2312
DOI	10.1016/j.neucom.2019.09.045
通讯作者	Wang, Fei-Yue(feiyue.wang@ia.ac.cn)
英文摘要	Although there has been a growing body of work for face recognition, it is still a challenging task for faces under occlusion with limited training samples. In this work, we propose a novel framework to address the problem of few-shot occluded face recognition. In particular, inspired by the human being's optic nerves characteristics that humans recognize the face under occlusion using contextual information rather than paying attention to the facial parts, we propose an effective feature extraction approach to capture the local and contextual information for face recognition. To enhance the robustness, we further introduce an adaptive fusion method to incorporate multiple features, including the proposed structural element feature, connected-granule labeling feature, and Reinforced Centrosymmetric Local Binary Pattern (RCSLBP). Final recognition is derived from the fusion of all classification results according to our proposed novel fusion method. Experimental results on three popular face image datasets of AR, Extended Yale B, and LFW demonstrate that our method performs better than many existing ones for few-shot face recognition in the presence of occlusion. (C) 2019 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[61806198] ; National Natural Science Foundation of China[61533019] ; National Natural Science Foundation of China[U1811463]
WOS关键词	CONSISTENT K-SVD ; DISCRIMINATIVE DICTIONARY ; SPARSE REPRESENTATION ; IMAGE ; ROBUST ; FEATURES ; OCCLUSION ; TEXTURE ; EXTRACTION ; REGRESSION
WOS研究方向	Computer Science
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000503433800003
资助机构	National Natural Science Foundation of China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/29475]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
通讯作者	Wang, Fei-Yue
作者单位	1.Xi An Jiao Tong Univ, Sch Software Engn, Xian 710049, Shaanxi, Peoples R China 2.Sun Yat Sen Univ, Sch Intelligent Syst Engn, Guangzhou 510275, Guangdong, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 4.Macau Univ Sci & Technol, Inst Syst Engn, Macau 999078, Peoples R China
推荐引用方式 GB/T 7714	Zheng, Wenbo,Gou, Chao,Wang, Fei-Yue. A novel approach inspired by optic nerve characteristics for few-shot occluded face recognition[J]. NEUROCOMPUTING,2020,376:25-41.
APA	Zheng, Wenbo,Gou, Chao,&Wang, Fei-Yue.(2020).A novel approach inspired by optic nerve characteristics for few-shot occluded face recognition.NEUROCOMPUTING,376,25-41.
MLA	Zheng, Wenbo,et al."A novel approach inspired by optic nerve characteristics for few-shot occluded face recognition".NEUROCOMPUTING 376(2020):25-41.