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Recent advances on singlemodal and multimodal face recognition : A survey

Zhou,H, Mian,A, Wei,L, Creighton,D, Hossny,M and Nahavandi,S 2014, Recent advances on singlemodal and multimodal face recognition : A survey, IEEE Transactions on Human-Machine Systems, vol. 44, no. 6, pp. 701-716, doi: 10.1109/THMS.2014.2340578.

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Title Recent advances on singlemodal and multimodal face recognition : A survey
Author(s) Zhou,HORCID iD for Zhou,H orcid.org/0000-0001-5009-4330
Mian,A
Wei,LORCID iD for Wei,L orcid.org/0000-0001-8267-0283
Creighton,DORCID iD for Creighton,D orcid.org/0000-0002-9217-1231
Hossny,MORCID iD for Hossny,M orcid.org/0000-0002-1593-6296
Nahavandi,SORCID iD for Nahavandi,S orcid.org/0000-0002-0360-5270
Journal name IEEE Transactions on Human-Machine Systems
Volume number 44
Issue number 6
Start page 701
End page 716
Total pages 16
Publisher Institute of Electrical and Electronics Engineers Inc
Place of publication Piscataway, NJ
Publication date 2014-12-01
ISSN 2168-2291
Keyword(s) 3-D
Face recognition
infrared
multimodal
singlemodal
survey
visual
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Cybernetics
Computer Science
THERMAL INFRARED IMAGERY
PHYSIOLOGICAL INFORMATION
FACIAL EXPRESSION
LINEAR PROJECTION
3D
FUSION
DEPTH
INVARIANT
MODEL
Summary High performance for face recognition systems occurs in controlled environments and degrades with variations in illumination, facial expression, and pose. Efforts have been made to explore alternate face modalities such as infrared (IR) and 3-D for face recognition. Studies also demonstrate that fusion of multiple face modalities improve performance as compared with singlemodal face recognition. This paper categorizes these algorithms into singlemodal and multimodal face recognition and evaluates methods within each category via detailed descriptions of representative work and summarizations in tables. Advantages and disadvantages of each modality for face recognition are analyzed. In addition, face databases and system evaluations are also covered.
Language eng
DOI 10.1109/THMS.2014.2340578
Field of Research 080111 Virtual Reality and Related Simulation
080109 Pattern Recognition and Data Mining
080104 Computer Vision
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, Institute of Electrical and Electronics Engineers Inc
Persistent URL http://hdl.handle.net/10536/DRO/DU:30071496

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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Citation counts: TR Web of Science Citation Count  Cited 16 times in TR Web of Science
Scopus Citation Count Cited 26 times in Scopus
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Created: Tue, 21 Apr 2015, 15:44:58 EST

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