Feature extraction and classification stage on facial expression : A review
Human facial expression becomes an important technology in recent years. As information technology and networks have grown, identification and authentication have become more frequent in people's daily lives, especially using biometric technology. Human facial recognition involves face detectio...
| Main Authors: | , , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2022
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/39334/1/Feature%20extraction%20and%20classification%20stage%20on%20facial%20expression_A%20review.pdf http://umpir.ump.edu.my/id/eprint/39334/2/Feature%20extraction%20and%20classification%20stage%20on%20facial%20expression_A%20review_ABS.pdf |
| _version_ | 1825815276833210368 |
|---|---|
| author | Shidiq, Muchamad Bachram Ernawan, Ferda Khubrani, Mousa Mohammed Nugroho, Fajar Agung |
| author_facet | Shidiq, Muchamad Bachram Ernawan, Ferda Khubrani, Mousa Mohammed Nugroho, Fajar Agung |
| author_sort | Shidiq, Muchamad Bachram |
| collection | UMP |
| description | Human facial expression becomes an important technology in recent years. As information technology and networks have grown, identification and authentication have become more frequent in people's daily lives, especially using biometric technology. Human facial recognition involves face detection, feature extraction, and classification. A lot of experiments showed that there are various techniques for extracting facial features and classifying facial expressions. This paper reviews and analyze the various optimization techniques on extract feature and classification stage for human facial expression recognition. This review will compare two kinds of extract features methods and one classification method. The first technique of extracting features is the optimization technique using the K-Mean algorithm, which helps to increase recognition accuracy. The second extract feature is an optimization technique using improved Gradient Local Ternary Pattern (GLTP) which is beneficial for computational resources efficiency. Lastly, the optimization technique for image classification using a three-staged Support Vector Machine (SVM) is very helpful for increasing accuracy and eliminating error. The modified GLTP is able to obtain an accuracy of 97%. |
| first_indexed | 2024-03-06T13:11:06Z |
| format | Conference or Workshop Item |
| id | UMPir39334 |
| institution | Universiti Malaysia Pahang |
| language | English English |
| last_indexed | 2024-03-06T13:11:06Z |
| publishDate | 2022 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| record_format | dspace |
| spelling | UMPir393342023-11-20T06:47:25Z http://umpir.ump.edu.my/id/eprint/39334/ Feature extraction and classification stage on facial expression : A review Shidiq, Muchamad Bachram Ernawan, Ferda Khubrani, Mousa Mohammed Nugroho, Fajar Agung QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Human facial expression becomes an important technology in recent years. As information technology and networks have grown, identification and authentication have become more frequent in people's daily lives, especially using biometric technology. Human facial recognition involves face detection, feature extraction, and classification. A lot of experiments showed that there are various techniques for extracting facial features and classifying facial expressions. This paper reviews and analyze the various optimization techniques on extract feature and classification stage for human facial expression recognition. This review will compare two kinds of extract features methods and one classification method. The first technique of extracting features is the optimization technique using the K-Mean algorithm, which helps to increase recognition accuracy. The second extract feature is an optimization technique using improved Gradient Local Ternary Pattern (GLTP) which is beneficial for computational resources efficiency. Lastly, the optimization technique for image classification using a three-staged Support Vector Machine (SVM) is very helpful for increasing accuracy and eliminating error. The modified GLTP is able to obtain an accuracy of 97%. Institute of Electrical and Electronics Engineers Inc. 2022-09 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39334/1/Feature%20extraction%20and%20classification%20stage%20on%20facial%20expression_A%20review.pdf pdf en http://umpir.ump.edu.my/id/eprint/39334/2/Feature%20extraction%20and%20classification%20stage%20on%20facial%20expression_A%20review_ABS.pdf Shidiq, Muchamad Bachram and Ernawan, Ferda and Khubrani, Mousa Mohammed and Nugroho, Fajar Agung (2022) Feature extraction and classification stage on facial expression : A review. In: Proceedings - International Conference on Informatics and Computational Sciences; 6th International Conference on Informatics and Computational Sciences, ICICoS 2022 , 28-29 September 2022 , Virtual, Online. pp. 152-156., 2022 (183902). ISSN 2767-7087 ISBN 978-166546099-6 (Published) https://doi.org/10.1109/ICICoS56336.2022.9930545 |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) Shidiq, Muchamad Bachram Ernawan, Ferda Khubrani, Mousa Mohammed Nugroho, Fajar Agung Feature extraction and classification stage on facial expression : A review |
| title | Feature extraction and classification stage on facial expression : A review |
| title_full | Feature extraction and classification stage on facial expression : A review |
| title_fullStr | Feature extraction and classification stage on facial expression : A review |
| title_full_unstemmed | Feature extraction and classification stage on facial expression : A review |
| title_short | Feature extraction and classification stage on facial expression : A review |
| title_sort | feature extraction and classification stage on facial expression a review |
| topic | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) TA Engineering (General). Civil engineering (General) |
| url | http://umpir.ump.edu.my/id/eprint/39334/1/Feature%20extraction%20and%20classification%20stage%20on%20facial%20expression_A%20review.pdf http://umpir.ump.edu.my/id/eprint/39334/2/Feature%20extraction%20and%20classification%20stage%20on%20facial%20expression_A%20review_ABS.pdf |
| work_keys_str_mv | AT shidiqmuchamadbachram featureextractionandclassificationstageonfacialexpressionareview AT ernawanferda featureextractionandclassificationstageonfacialexpressionareview AT khubranimousamohammed featureextractionandclassificationstageonfacialexpressionareview AT nugrohofajaragung featureextractionandclassificationstageonfacialexpressionareview |