3D facial expression intensity measurement analysis
This study used 3D distance vector measurements as the facial feature to classify six basic expressions and the distance vectors are chosen based on Facial Action Coding System (FACS) component, facial action units (AUs).The statistical values are calculated and analyze to determine the AUs involve...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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2017
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/22793/1/ICOCI%202017%2043-48.pdf |
| _version_ | 1825804815399124992 |
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| author | Cheong, Alicia Chiek Ying Ujir, Hamimah Hipiny, Irwandi |
| author_facet | Cheong, Alicia Chiek Ying Ujir, Hamimah Hipiny, Irwandi |
| author_sort | Cheong, Alicia Chiek Ying |
| collection | UUM |
| description | This study used 3D distance vector measurements as the facial feature to classify six basic expressions and the distance vectors are chosen
based on Facial Action Coding System (FACS) component, facial action units (AUs).The statistical values are calculated and analyze to determine the AUs involved in facial expression and distance vectors to be taken into account to measure the intensity of each facial expression in a quantitative manner.As a result, 14 facial points are classified as significant in facial expression classification.Those facial points are in the eye, eyebrow and mouth region only. This work reveals that it is not necessary to rely on all facial feature points in estimating facial expression intensity.For Sad expression, the random mean and standard deviation of distance measurements do not indicate which AU should be taken into account to classify this expression. |
| first_indexed | 2024-07-04T06:21:53Z |
| format | Conference or Workshop Item |
| id | uum-22793 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:21:53Z |
| publishDate | 2017 |
| record_format | eprints |
| spelling | uum-227932017-07-26T07:33:20Z https://repo.uum.edu.my/id/eprint/22793/ 3D facial expression intensity measurement analysis Cheong, Alicia Chiek Ying Ujir, Hamimah Hipiny, Irwandi QA75 Electronic computers. Computer science This study used 3D distance vector measurements as the facial feature to classify six basic expressions and the distance vectors are chosen based on Facial Action Coding System (FACS) component, facial action units (AUs).The statistical values are calculated and analyze to determine the AUs involved in facial expression and distance vectors to be taken into account to measure the intensity of each facial expression in a quantitative manner.As a result, 14 facial points are classified as significant in facial expression classification.Those facial points are in the eye, eyebrow and mouth region only. This work reveals that it is not necessary to rely on all facial feature points in estimating facial expression intensity.For Sad expression, the random mean and standard deviation of distance measurements do not indicate which AU should be taken into account to classify this expression. 2017 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/22793/1/ICOCI%202017%2043-48.pdf Cheong, Alicia Chiek Ying and Ujir, Hamimah and Hipiny, Irwandi (2017) 3D facial expression intensity measurement analysis. In: 6th International Conference on Computing & Informatics (ICOCI2017), 25 - 27 April 2017, Kuala Lumpur. http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap01e/PID143-43-48e.pdf |
| spellingShingle | QA75 Electronic computers. Computer science Cheong, Alicia Chiek Ying Ujir, Hamimah Hipiny, Irwandi 3D facial expression intensity measurement analysis |
| title | 3D facial expression intensity measurement analysis |
| title_full | 3D facial expression intensity measurement analysis |
| title_fullStr | 3D facial expression intensity measurement analysis |
| title_full_unstemmed | 3D facial expression intensity measurement analysis |
| title_short | 3D facial expression intensity measurement analysis |
| title_sort | 3d facial expression intensity measurement analysis |
| topic | QA75 Electronic computers. Computer science |
| url | https://repo.uum.edu.my/id/eprint/22793/1/ICOCI%202017%2043-48.pdf |
| work_keys_str_mv | AT cheongaliciachiekying 3dfacialexpressionintensitymeasurementanalysis AT ujirhamimah 3dfacialexpressionintensitymeasurementanalysis AT hipinyirwandi 3dfacialexpressionintensitymeasurementanalysis |