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Automated Facial Expression System using PCA Algorithm

by Noreen Akram, Naeem Abbas
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 9
Year of Publication: 2018
Authors: Noreen Akram, Naeem Abbas
10.5120/ijca2018917681

Noreen Akram, Naeem Abbas . Automated Facial Expression System using PCA Algorithm. International Journal of Computer Applications. 182, 9 ( Aug 2018), 32-36. DOI=10.5120/ijca2018917681

@article{ 10.5120/ijca2018917681,
author = { Noreen Akram, Naeem Abbas },
title = { Automated Facial Expression System using PCA Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2018 },
volume = { 182 },
number = { 9 },
month = { Aug },
year = { 2018 },
issn = { 0975-8887 },
pages = { 32-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number9/29849-2018917681/ },
doi = { 10.5120/ijca2018917681 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:10:54.141434+05:30
%A Noreen Akram
%A Naeem Abbas
%T Automated Facial Expression System using PCA Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 9
%P 32-36
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Facial expressions are important aspect of human communication. Human beings can identify facial expressions without any difficulty but this job is very difficult for computers to do. The purpose of this research paper is to develop such system which can identify the facial expressions of human beings in real time with minimum error. For the FER (i.e. Facial Expression Recognition), three steps are used; face detection, facial feature extraction and finally classification of expression. Technique used for facial feature extraction is Principal Component Analysis (PCA).

References
  1. K. Matsuno, C-W Lee, S. Kimura, S. Tsuji. Automatic Recognition of Human Facial Expressions. In Proceeding of the Fifth International Conference on Computer Vision, Pp. 352-359. 1995.
  2. Anastasios C. Koutlas, Dimitrios I. Fotiadis “A Region Based Methodology for Facial Expression Recognition” page 1.
  3. Hong-Bo Deng, Lian-Wen Jin, Li-Xin Zhen, Jian-Cheng Huang “A  New Facial Expression Recognition Method Based on Local Gabor Filter Bank and PCA plus LDA”, International Journal of Information Technology Vol. 11 No. 11-2005.
  4. Yang, J., Zhang, D., 2004, “Two-dimensional pca: a new approach to appearance-based face representation and recognition”, IEEE Transactions on Image Processing, Vol.26, No.1, pp. 131–137, Jan 2004.
  5. Turk, "Face Recognition using eigenfaces," in Computer Society Conference, IEEE, Pentland, Queensland, pp.586-591, 1991.
  6. http://www.kasrl.org/jaffe.html
  7. Louis Asiedu1, Felix .O. Mettle2, Ezekiel N. N. Nortey “Recognition of Facial Expression Using Principal Component Analysis and Singular Value Decomposition” International Journal of Statistics and Systems ISSN 0973-2675 Volume 9, Number 2 (2014), pp. 157-172 Department of Statistics, University of Ghana
Index Terms

Computer Science
Information Sciences

Keywords

Facial expression recognition PCA (Principal Component Analysis) Japanese Female Facial Expression (JAFFE) database

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