Real-time facial expression recognition system (FERS)

Real-Time Facial Expression Recognition System (FERS) is developed to recognize facial expressions.Findings claiming that humans display their emotions most expressively through face expressions and body gestures. Humans are more likely to consider computers to be human like when those computers und...

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Main Author: Thelehaswary, Appalasamy
Format: Undergraduates Project Papers
Language:English
Published: 2011
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/4334/1/THELEHAESWARY_APPALASAMY.PDF
http://umpir.ump.edu.my/id/eprint/4334/
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Institution: Universiti Malaysia Pahang
Language: English
id my.ump.umpir.4334
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spelling my.ump.umpir.43342021-07-16T05:05:35Z http://umpir.ump.edu.my/id/eprint/4334/ Real-time facial expression recognition system (FERS) Thelehaswary, Appalasamy TA Engineering (General). Civil engineering (General) Real-Time Facial Expression Recognition System (FERS) is developed to recognize facial expressions.Findings claiming that humans display their emotions most expressively through face expressions and body gestures. Humans are more likely to consider computers to be human like when those computers understand and display appropriate nonverbal communicative behaviour.So,the interaction between humans and computers will be-more natural if computers are able to understand the nonverbal behaviour of their 'human counterparts and recognize their affective state. Therefore,this project is carried out to build a prototype to recognize facial expressions. Evolutionary methodology was implemented in this system design by using several image processing techniques include imageacquisition,image enhancement (or known as pre-processing stages)and feature extraction.Hundred and fifty four sample,data of human faces in the range of 18 to 26 years old is tested.The system first applies some pre-processing stages to enhance the input image and reduce the noise.The face boundary will then be detected. The region of interest(i.e. mouth and eyes)will be determined,from which,features will be extracted. Finally, the face'will be -classified into-one of three different classes using the Kmeans method based on the features extracted.The method was applied and tested on a datase-of 1-54 images of faces and -the success rate obtained was 94.-80%. 2011-05 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/4334/1/THELEHAESWARY_APPALASAMY.PDF Thelehaswary, Appalasamy (2011) Real-time facial expression recognition system (FERS). Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang.
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Thelehaswary, Appalasamy
Real-time facial expression recognition system (FERS)
description Real-Time Facial Expression Recognition System (FERS) is developed to recognize facial expressions.Findings claiming that humans display their emotions most expressively through face expressions and body gestures. Humans are more likely to consider computers to be human like when those computers understand and display appropriate nonverbal communicative behaviour.So,the interaction between humans and computers will be-more natural if computers are able to understand the nonverbal behaviour of their 'human counterparts and recognize their affective state. Therefore,this project is carried out to build a prototype to recognize facial expressions. Evolutionary methodology was implemented in this system design by using several image processing techniques include imageacquisition,image enhancement (or known as pre-processing stages)and feature extraction.Hundred and fifty four sample,data of human faces in the range of 18 to 26 years old is tested.The system first applies some pre-processing stages to enhance the input image and reduce the noise.The face boundary will then be detected. The region of interest(i.e. mouth and eyes)will be determined,from which,features will be extracted. Finally, the face'will be -classified into-one of three different classes using the Kmeans method based on the features extracted.The method was applied and tested on a datase-of 1-54 images of faces and -the success rate obtained was 94.-80%.
format Undergraduates Project Papers
author Thelehaswary, Appalasamy
author_facet Thelehaswary, Appalasamy
author_sort Thelehaswary, Appalasamy
title Real-time facial expression recognition system (FERS)
title_short Real-time facial expression recognition system (FERS)
title_full Real-time facial expression recognition system (FERS)
title_fullStr Real-time facial expression recognition system (FERS)
title_full_unstemmed Real-time facial expression recognition system (FERS)
title_sort real-time facial expression recognition system (fers)
publishDate 2011
url http://umpir.ump.edu.my/id/eprint/4334/1/THELEHAESWARY_APPALASAMY.PDF
http://umpir.ump.edu.my/id/eprint/4334/
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