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Demographic Analysis from Biometric Data: Achievements, Challenges, and New Frontiers
Sun, Yunlian1,2; Zhang, Man1; Sun, Zhenan1; Tan, Tieniu1
Source PublicationIEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
2018-02-01
Volume40Issue:2Pages:332-351
SubtypeArticle
AbstractBiometrics is the technique of automatically recognizing individuals based on their biological or behavioral characteristics. Various biometric traits have been introduced and widely investigated, including fingerprint, iris, face, voice, palmprint, gait and so forth. Apart from identity, biometric data may convey various other personal information, covering affect, age, gender, race, accent, handedness, height, weight, etc. Among these, analysis of demographics (age, gender, and race) has received tremendous attention owing to its wide real-world applications, with significant efforts devoted and great progress achieved. This survey first presents biometric demographic analysis from the standpoint of human perception, then provides a comprehensive overview of state-of-the-art advances in automated estimation from both academia and industry. Despite these advances, a number of challenging issues continue to inhibit its full potential. We second discuss these open problems, and finally provide an outlook into the future of this very active field of research by sharing some promising opportunities.
KeywordDemographic Estimation Biometrics Human Age Estimation Gender Classification Race Recognition
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TPAMI.2017.2669035
WOS KeywordHUMAN AGE ESTIMATION ; SUPPORT VECTOR MACHINES ; GENDER CLASSIFICATION METHODS ; LOCAL BINARY PATTERNS ; FACE IMAGES ; SOFT BIOMETRICS ; TELEPHONE APPLICATIONS ; SEX IDENTIFICATION ; BIOLOGICAL MOTION ; GAIT SEQUENCES
Indexed BySCI ; SSCI
Language英语
Funding OrganizationNational Key Research and Development Program of China(2016YFB1001000) ; National Natural Science Foundation of China(61603391 ; 61603385)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000422706000006
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15354
Collection智能感知与计算研究中心
09年以前成果
Affiliation1.Chinese Acad Sci, Ctr Res Intelligent Percept & Comp, Natl Lab Pattern Recognit, Inst Automat,CAS Ctr Excellence Brain Sci & Intel, Beijing 100190, Peoples R China
2.Nanjing Univ Sci & Technol, Sch Comp Sci & Engn, Nanjing 210094, Jiangsu, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Sun, Yunlian,Zhang, Man,Sun, Zhenan,et al. Demographic Analysis from Biometric Data: Achievements, Challenges, and New Frontiers[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2018,40(2):332-351.
APA Sun, Yunlian,Zhang, Man,Sun, Zhenan,&Tan, Tieniu.(2018).Demographic Analysis from Biometric Data: Achievements, Challenges, and New Frontiers.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,40(2),332-351.
MLA Sun, Yunlian,et al."Demographic Analysis from Biometric Data: Achievements, Challenges, and New Frontiers".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 40.2(2018):332-351.
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