Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion
Link to publisher's homepage at http://ieeexplore.ieee.org/
Saved in:
Main Authors: | , , , , , , |
---|---|
Other Authors: | |
Format: | Working Paper |
Language: | English |
Published: |
IEEE Conference Publications
2014
|
Subjects: | |
Online Access: | http://dspace.unimap.edu.my:80/dspace/handle/123456789/33702 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Malaysia Perlis |
Language: | English |
id |
my.unimap-33702 |
---|---|
record_format |
dspace |
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 |