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2018 | OriginalPaper | Chapter

Facial Expression Recognition Using 2DPCA on Segmented Images

Authors : Dewan Imdadul Islam, S. R. Ngamwal Anal, Aloke Datta

Published in: Advanced Computational and Communication Paradigms

Publisher: Springer Singapore

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Abstract

In this article, a facial expression recognition technique has been proposed. In this method, initially, a face image is segmented into different sub-images like left eye, right eye, mouth, nose, etc. Then, two-dimensional principal component analysis (2DPCA)-based transformation is performed on each sub-image separately to extract the features. Lastly, classification operation is made to categorize the expression of faces. To demonstrate the effectiveness of the proposed method, results are compared with other existing PCA- and 2DPCA-based methods in terms of overall classification accuracy. Results for the proposed method are found to be encouraging.

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Metadata
Title
Facial Expression Recognition Using 2DPCA on Segmented Images
Authors
Dewan Imdadul Islam
S. R. Ngamwal Anal
Aloke Datta
Copyright Year
2018
Publisher
Springer Singapore
Book
Advanced Computational and Communication Paradigms

Print ISBN: 978-981-10-8236-8

Electronic ISBN: 978-981-10-8237-5

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-8237-5_28