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Personalized human emotion classification using genetic algorithm

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Main Authors: Mohd Rizon, Hazry, Desa, Karthigayan, M., Nagarajan, Ramachandran, Alajlan, N., Sazali, Yaacob, Prof. Dr., Nor Azmi, Johari, Ina Suryani, Ab Rahim
Format: Working Paper
Language:English
Published: Institute of Electrical and Elctronics Engineering (IEEE) 2010
Subjects:
Classification
Classification of emotions
Ellipse fitting
Fitness functions
Human emotion
Lip features
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/8686
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spelling my.unimap-86862014-05-22T08:31:22Z Personalized human emotion classification using genetic algorithm Mohd Rizon Hazry, Desa Karthigayan, M. Nagarajan, Ramachandran Alajlan, N. Sazali, Yaacob, Prof. Dr. Nor Azmi, Johari Ina Suryani, Ab Rahim Classification Classification of emotions Ellipse fitting Fitness functions Human emotion Lip features Link to publisher's homepage at http://ieeexplore.ieee.org/ In this paper, lip and eye features are applied to classify the human emotion through a set of irregular and regular ellipse fitting equations using Genetic algorithm (GA). South East Asian face is considered in this study. All six universally accepted emotions and one neutral are considered for classifications. The method which is fastest in extracting lip features is adopted in this study. Observation of various emotions of the subject lead to an unique characteristic of lips and eye. GA is adopted to optimize irregular ellipse and regular ellipse characteristics of the lip and eye features in each emotion respectively. 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 emotion are listed. One ellipse based fitness function is proposed for eye. The GA method approach has achieved reasonably successful classification of emotion. While performing classification, optimized values can mess or overlap with other emotions range. In order to overcome the overlapping problem between the emotions and at the same time to improve the classification, a neural network (NN) approach is implemented. The GA-NN based process exhibits a range of 83% - 90% classification of the emotion from the optimized feature of top lip, bottom lip and eye. 2010-08-16T03:23:10Z 2010-08-16T03:23:10Z 2009-07-05 Working Paper p.224-228 978-0-7695-3734-4 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5230751&tag=1 http://hdl.handle.net/123456789/8686 en Proceedings of the 2nd International Conference in Visualisation (VIZ) 2009 Institute of Electrical and Elctronics 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 Classification
Classification of emotions
Ellipse fitting
Fitness functions
Human emotion
Lip features
spellingShingle Classification
Classification of emotions
Ellipse fitting
Fitness functions
Human emotion
Lip features
Mohd Rizon
Hazry, Desa
Karthigayan, M.
Nagarajan, Ramachandran
Alajlan, N.
Sazali, Yaacob, Prof. Dr.
Nor Azmi, Johari
Ina Suryani, Ab Rahim
Personalized human emotion classification using genetic algorithm
description Link to publisher's homepage at http://ieeexplore.ieee.org/
format Working Paper
author Mohd Rizon
Hazry, Desa
Karthigayan, M.
Nagarajan, Ramachandran
Alajlan, N.
Sazali, Yaacob, Prof. Dr.
Nor Azmi, Johari
Ina Suryani, Ab Rahim
author_facet Mohd Rizon
Hazry, Desa
Karthigayan, M.
Nagarajan, Ramachandran
Alajlan, N.
Sazali, Yaacob, Prof. Dr.
Nor Azmi, Johari
Ina Suryani, Ab Rahim
author_sort Mohd Rizon
title Personalized human emotion classification using genetic algorithm
title_short Personalized human emotion classification using genetic algorithm
title_full Personalized human emotion classification using genetic algorithm
title_fullStr Personalized human emotion classification using genetic algorithm
title_full_unstemmed Personalized human emotion classification using genetic algorithm
title_sort personalized human emotion classification using genetic algorithm
publisher Institute of Electrical and Elctronics Engineering (IEEE)
publishDate 2010
url http://dspace.unimap.edu.my/xmlui/handle/123456789/8686
_version_ 1643789250225766400
score 13.209306

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