NDLI: Expression recognition based on EPCA and SVM

Content Provider	IEEE Xplore Digital Library
Author	Yani Zhu Jiatao Song Xiaobo Ren Meng Chen
Copyright Year	2008
Description	Author affiliation: Dept. of Sci. & Technol., Hangzhou Dianzi Univ., Hangzhou (Yani Zhu)
Abstract	Equable principal component analysis (EPCA) is a powerful technique of feature extracting. It can reduce a large set of correlated variables to a smaller number of uncorrelated components. Support vector machines (SVM) is a novel pattern classification approach. It is very efficient in solving clustering problems that are not linearly separable. This paper presents a method of expression recognition based on the EPCA and SVM. According to the EPCA extracting feature, this paper recognizes expression with SVM. The multi-class classification problem is solved by the approach of one-against all SVM classifier. Experiments of human who participates in test have been trained or not are performed on the JAFFE and Yale database. And compared to the nearest classifier, the EPCA and SVM can get better recognition ratio. Therefore, it is feasible to apply EPCA and SVM to expression recognition.
Starting Page	8516
Ending Page	8520
File Size	335359
Page Count	5
File Format	PDF
ISBN	9781424421138
DOI	10.1109/WCICA.2008.4594266
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Feature extraction Training Classification algorithms Principal component analysis Face Signal processing algorithms nearest classifier expression recognition EPCA SVM
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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