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Multi-label approach for human-face classification

Mohammed, Ahmed Abdulateef, Sajjanhar, Atul and Nasierding, Gulisong 2015, Multi-label approach for human-face classification, in CISP 2015 : Proceedings of the 8th International Congress on Image and Signal Processing, IEEE, Piscataway, N.J., pp. 648-653, doi: 10.1109/CISP.2015.7407958.

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Title Multi-label approach for human-face classification
Author(s) Mohammed, Ahmed Abdulateef
Sajjanhar, AtulORCID iD for Sajjanhar, Atul orcid.org/0000-0002-0445-0573
Nasierding, Gulisong
Conference name Image and Signal Processing. International Congress (8th : 2015 : Shenyang, China)
Conference location Shenyang, China
Conference dates 14-16 Oct. 2015
Title of proceedings CISP 2015 : Proceedings of the 8th International Congress on Image and Signal Processing
Publication date 2015
Start page 648
End page 653
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) face classification
linear discriminant analysis
multi-label classification
principal component analysis
Summary Single-label classification models have been widely used for human-face classification. In this paper, we present a multi-label classification approach for human-face classification. Multi-label classification is more appropriate in the real world because a human-face can be associated with multiple labels. Demographic information can be derived and utilized along with facial expression in the field of face classification to assist with multi label classification. Gabor filters; Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) methods, are used to extract and project representative demographic information from facial images. For evaluation, five classification algorithms were used. We evaluate the proposed approach by performing experiments on Yale face images database. Results show the effectiveness of multi-label classification algorithms.
ISBN 9781467390989
Language eng
DOI 10.1109/CISP.2015.7407958
Field of Research 080106 Image Processing
Socio Economic Objective 890201 Application Software Packages (excl. Computer Games)
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30081750

Document type: Conference Paper
Collection: School of Information Technology
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