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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...

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Main Authors: Cheong, Alicia Chiek Ying, Ujir, Hamimah, Hipiny, Irwandi
Format: Conference or Workshop Item
Language:English
Published: 2017
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://repo.uum.edu.my/22793/1/ICOCI%202017%2043-48.pdf
http://repo.uum.edu.my/22793/
http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap01e/PID143-43-48e.pdf
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spelling my.uum.repo.227932017-07-26T07:33:20Z http://repo.uum.edu.my/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 http://repo.uum.edu.my/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
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Cheong, Alicia Chiek Ying
Ujir, Hamimah
Hipiny, Irwandi
3D facial expression intensity measurement analysis
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.
format Conference or Workshop Item
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
title 3D facial expression intensity measurement analysis
title_short 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_sort 3d facial expression intensity measurement analysis
publishDate 2017
url http://repo.uum.edu.my/22793/1/ICOCI%202017%2043-48.pdf
http://repo.uum.edu.my/22793/
http://icoci.cms.net.my/PROCEEDINGS/2017/Pdf_Version_Chap01e/PID143-43-48e.pdf
_version_ 1644283618029207552
score 13.211869

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