CASIA-Face-Africa: A Large-Scale African Face Image Database

doi:10.1109/TIFS.2021.3080496

CORC > 自动化研究所 > 中国科学院自动化研究所 > 智能感知与计算研究中心

	CASIA-Face-Africa: A Large-Scale African Face Image Database
	Muhammad, Jawad 1,2; Wang, Yunlong 1,2; Wang, Caiyong 3,4; Zhang, Kunbo 1,2; Sun, Zhenan 1,2
刊名	IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
	2021
卷号	16 页码:3634-3646
关键词	Face recognition Image databases Internet Cameras Image recognition Skin Face detection African face recognition racial bias face image database
ISSN号	1556-6013
DOI	10.1109/TIFS.2021.3080496
通讯作者	Sun, Zhenan(znsun@nlpr.ia.ac.cn)
英文摘要	Face recognition is a popular and well-studied area with wide applications in our society. However, racial bias had been proven to be inherent in most State Of The Art (SOTA) face recognition systems. Many investigative studies on face recognition algorithms have reported higher false positive rates of African subjects cohorts than the other cohorts. Lack of large-scale African face image databases in public domain is one of the main restrictions in studying the racial bias problem of face recognition. To this end, we collect a face image database namely CASIA-Face-Africa which contains 38,546 images of 1,183 African subjects. Multi-spectral cameras are utilized to capture the face images under various illumination settings. Demographic attributes and facial expressions of the subjects are also carefully recorded. For landmark detection, each face image in the database is manually labeled with 68 facial keypoints. A group of evaluation protocols are constructed according to different applications, tasks, partitions and scenarios. The performances of SOTA face recognition algorithms without re-training are reported as baselines. The proposed database along with its face landmark annotations, evaluation protocols and preliminary results form a good benchmark to study the essential aspects of face biometrics for African subjects, especially face image preprocessing, face feature analysis and matching, facial expression recognition, sex/age estimation, ethnic classification, face image generation, etc. The database can be downloaded from our website.
WOS关键词	EIGENFACES
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号	WOS:000670544600009
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/45271]
专题	自动化研究所_智能感知与计算研究中心
通讯作者	Sun, Zhenan
作者单位	1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Res Intelligent Percept & Comp, Beijing 100190, Peoples R China 3.Beijing Univ Civil Engn & Architecture, Sch Elect & Informat Engn, Beijing 100044, Peoples R China 4.Beijing Key Lab Intelligent Proc Bldg Big Dat, Beijing 100044, Peoples R China
推荐引用方式 GB/T 7714	Muhammad, Jawad,Wang, Yunlong,Wang, Caiyong,et al. CASIA-Face-Africa: A Large-Scale African Face Image Database[J]. IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,2021,16:3634-3646.
APA	Muhammad, Jawad,Wang, Yunlong,Wang, Caiyong,Zhang, Kunbo,&Sun, Zhenan.(2021).CASIA-Face-Africa: A Large-Scale African Face Image Database.IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY,16,3634-3646.
MLA	Muhammad, Jawad,et al."CASIA-Face-Africa: A Large-Scale African Face Image Database".IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 16(2021):3634-3646.