A Comparison of Four Classification Algorithms for Facial Expression Recognition
Facial expression recognition (FER) has achieved an extreme role in research area since the 1990s. This paper provides a comparison approach for FER based on three feature selection methods which are correlation, gain ration, and information gain for determining the most distinguished features of fa...
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| Format: | Article |
| Language: | English |
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Erbil Polytechnic University
2020-06-01
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| Series: | Polytechnic Journal |
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| Online Access: | https://polytechnic-journal.epu.edu.iq/home/vol10/iss1/13 |
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| author | Hivi I. Dino Maiwan B. Abdulrazzaq |
| author_facet | Hivi I. Dino Maiwan B. Abdulrazzaq |
| author_sort | Hivi I. Dino |
| collection | DOAJ |
| description | Facial expression recognition (FER) has achieved an extreme role in research area since the 1990s. This
paper provides a comparison approach for FER based on three feature selection methods which are
correlation, gain ration, and information gain for determining the most distinguished features of face
images using multi-classification algorithms which are multilayer perceptron, Naïve Bayes, decision tree,
and K-nearest neighbor (KNN). These classifiers are used for the mission of expression recognition and
for comparing their proportional performance. The main aim of the provided approach is to determine the
most effective classifier based on minimum acceptable number of features by analyzing and comparing
their performance. The provided approach has been applied on CK+ dataset. The experimental results
show that KNN is proven to be better classifier with 91% accuracy using only 30 features. |
| format | Article |
| id | doaj-art-67be1edb34f24f26983c42df32b3e259 |
| institution | DOAJ |
| issn | 2707-7799 |
| language | English |
| publishDate | 2020-06-01 |
| publisher | Erbil Polytechnic University |
| record_format | Article |
| series | Polytechnic Journal |
| spelling | doaj-art-67be1edb34f24f26983c42df32b3e2592025-08-20T03:18:15ZengErbil Polytechnic UniversityPolytechnic Journal2707-77992020-06-011017480https://doi.org/10.25156/ptj.v10n1y2020.pp74-80A Comparison of Four Classification Algorithms for Facial Expression RecognitionHivi I. Dino0Maiwan B. Abdulrazzaq1Department of Computer Science, Faculty of Science, University of Zakho, Zakho, Kurdistan Region, IraqDepartment of Computer Science, Faculty of Science, University of Zakho, Zakho, Kurdistan Region, IraqFacial expression recognition (FER) has achieved an extreme role in research area since the 1990s. This paper provides a comparison approach for FER based on three feature selection methods which are correlation, gain ration, and information gain for determining the most distinguished features of face images using multi-classification algorithms which are multilayer perceptron, Naïve Bayes, decision tree, and K-nearest neighbor (KNN). These classifiers are used for the mission of expression recognition and for comparing their proportional performance. The main aim of the provided approach is to determine the most effective classifier based on minimum acceptable number of features by analyzing and comparing their performance. The provided approach has been applied on CK+ dataset. The experimental results show that KNN is proven to be better classifier with 91% accuracy using only 30 features.https://polytechnic-journal.epu.edu.iq/home/vol10/iss1/13correlation;facial expression recognition;feature selection;gain ratio;information gain |
| spellingShingle | Hivi I. Dino Maiwan B. Abdulrazzaq A Comparison of Four Classification Algorithms for Facial Expression Recognition Polytechnic Journal correlation; facial expression recognition; feature selection; gain ratio; information gain |
| title | A Comparison of Four Classification Algorithms for Facial Expression Recognition |
| title_full | A Comparison of Four Classification Algorithms for Facial Expression Recognition |
| title_fullStr | A Comparison of Four Classification Algorithms for Facial Expression Recognition |
| title_full_unstemmed | A Comparison of Four Classification Algorithms for Facial Expression Recognition |
| title_short | A Comparison of Four Classification Algorithms for Facial Expression Recognition |
| title_sort | comparison of four classification algorithms for facial expression recognition |
| topic | correlation; facial expression recognition; feature selection; gain ratio; information gain |
| url | https://polytechnic-journal.epu.edu.iq/home/vol10/iss1/13 |
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