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

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Main Authors: Karthigayan, Muthukaruppan, Mohamed, Rizon, Sazali, Yaacob, Prof. Dr., Nagarajan, Ramachandran, Sugisaka, Masanori, Mohd Rozailan, Mamat, Prof. Madya Dr., Hazry, Desa, Assoc. Prof. Dr.
Other Authors: karthigayan@ieee.org
Format: Working Paper
Language:English
Published: IEEE Conference Publications 2014
Subjects:
Feature extraction
Ellipse fitness function
Genetic algorithm
Emotion recognition
Fuzzy clustering
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33702
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spelling my.unimap-337022017-11-29T05:03:51Z Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion Karthigayan, Muthukaruppan Mohamed, Rizon Sazali, Yaacob, Prof. Dr. Nagarajan, Ramachandran Sugisaka, Masanori Mohd Rozailan, Mamat, Prof. Madya Dr. Hazry, Desa, Assoc. Prof. Dr. karthigayan@ieee.org s.yaacob@unimap.edu.my rozailan@unimap.edu.my hazry@unimap.edu.my Feature extraction Ellipse fitness function Genetic algorithm Emotion recognition Fuzzy clustering 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. 2014-04-15T03:11:25Z 2014-04-15T03:11:25Z 2007 Working Paper International Conference on Control, Automation and Systems, 2007, pages 1-5 978-89-950038-6-2 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33702 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4406868&tag=1 http://dx.doi.org/10.1109/ICCAS.2007.4406868 en IEEE Conference Publications
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 Feature extraction
Ellipse fitness function
Genetic algorithm
Emotion recognition
Fuzzy clustering
spellingShingle Feature extraction
Ellipse fitness function
Genetic algorithm
Emotion recognition
Fuzzy clustering
Karthigayan, Muthukaruppan
Mohamed, Rizon
Sazali, Yaacob, Prof. Dr.
Nagarajan, Ramachandran
Sugisaka, Masanori
Mohd Rozailan, Mamat, Prof. Madya Dr.
Hazry, Desa, Assoc. Prof. Dr.
Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion
description Link to publisher's homepage at http://ieeexplore.ieee.org/
author2 karthigayan@ieee.org
author_facet karthigayan@ieee.org
Karthigayan, Muthukaruppan
Mohamed, Rizon
Sazali, Yaacob, Prof. Dr.
Nagarajan, Ramachandran
Sugisaka, Masanori
Mohd Rozailan, Mamat, Prof. Madya Dr.
Hazry, Desa, Assoc. Prof. Dr.
format Working Paper
author Karthigayan, Muthukaruppan
Mohamed, Rizon
Sazali, Yaacob, Prof. Dr.
Nagarajan, Ramachandran
Sugisaka, Masanori
Mohd Rozailan, Mamat, Prof. Madya Dr.
Hazry, Desa, Assoc. Prof. Dr.
author_sort Karthigayan, Muthukaruppan
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 IEEE Conference Publications
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/33702
_version_ 1643802749501964288
score 13.222552

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