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Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion

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Main Authors: Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Sazali, Yaacob, Ramachandran, Nagarajan, Masanori, Sugisaka, Mohd Rozailan, Mamat
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineering (IEEE) 2009
Subjects:
Emotion recognition
Face recognition
Fuzzy set theory
Genetic algorithms
Recognition system
Detectors
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/6677
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spelling my.unimap-66772010-11-23T06:33:14Z Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion Muthukaruppan, Karthigayan Mohd Rizon, Mohamed Juhari Sazali, Yaacob Ramachandran, Nagarajan Masanori, Sugisaka Mohd Rozailan, Mamat Emotion recognition Face recognition Fuzzy set theory Genetic algorithms Recognition system Detectors Link to publisher's homepage at http://ieeexplore.ieee.org In this paper, lip and eye features are applied to classify the human emotion using a set of irregular and regular ellipse fitting equations using genetic algorithm (GA). A South East Asian face is considered in this study. The parameters relating the face emotions, in either case, are entirely different. All six universally accepted emotions and one neutral are considered for classifications. The method which is fastest in extracting lip and eye features is adopted in this study. Observation of various emotions of the subject lead to unique characteristic of lips and eyes. GA is adopted to optimize irregular ellipse characteristics of the lip and eye features in each emotion. That is, the top portion of lip configuration is a part of one ellipse and the bottom of different ellipse. Two ellipse based fitness equations are proposed for the lip configuration and relevant parameters that define the emotions are listed. One ellipse based fitness function is proposed for the eye configuration. The GA method has achieved reasonably successful classification of emotion. In some emotions classification, optimized data values of one emotion are messed or overlapped to other emotion ranges. In order to overcome the overlapping problem between the emotion optimized values and at the same time to improve the classification, a fuzzy clustering method (FCM) of approach has been implemented to offer better classification. The GA-FCM approach offers a reasonably good classification within the ranges of clusters. 2009-08-06T06:58:48Z 2009-08-06T06:58:48Z 2007-10 Article p.1-5 978-89-950038-6-2 http://ieeexplore.ieee.org/xpls/abs_all.jsp?=&arnumber=4406868 http://hdl.handle.net/123456789/6677 en International Conference on Control, Automation and Systems (ICCAS 2007) Institute of Electrical and Electronics Engineering (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Emotion recognition
Face recognition
Fuzzy set theory
Genetic algorithms
Recognition system
Detectors
spellingShingle Emotion recognition
Face recognition
Fuzzy set theory
Genetic algorithms
Recognition system
Detectors
Muthukaruppan, Karthigayan
Mohd Rizon, Mohamed Juhari
Sazali, Yaacob
Ramachandran, Nagarajan
Masanori, Sugisaka
Mohd Rozailan, Mamat
Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion
description Link to publisher's homepage at http://ieeexplore.ieee.org
format Article
author Muthukaruppan, Karthigayan
Mohd Rizon, Mohamed Juhari
Sazali, Yaacob
Ramachandran, Nagarajan
Masanori, Sugisaka
Mohd Rozailan, Mamat
author_facet Muthukaruppan, Karthigayan
Mohd Rizon, Mohamed Juhari
Sazali, Yaacob
Ramachandran, Nagarajan
Masanori, Sugisaka
Mohd Rozailan, Mamat
author_sort Muthukaruppan, Karthigayan
title Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion
title_short Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion
title_full Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion
title_fullStr Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion
title_full_unstemmed Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion
title_sort fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion
publisher Institute of Electrical and Electronics Engineering (IEEE)
publishDate 2009
url http://dspace.unimap.edu.my/xmlui/handle/123456789/6677
_version_ 1643788575941066752
score 13.214268

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