Development of a personified face emotion recognition technique using fitness function

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Main Authors: Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Ramachandran, Nagarajan, Masanori, Sugisaka, Sazali, Yaacob, Mohd Rozailan, Mamat, Hazry, Desa
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Language:English
Published: Springer Japan 2009
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Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/6688
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spelling my.unimap-66882009-08-06T12:31:27Z Development of a personified face emotion recognition technique using fitness function Muthukaruppan, Karthigayan Mohd Rizon, Mohamed Juhari Ramachandran, Nagarajan Masanori, Sugisaka Sazali, Yaacob Mohd Rozailan, Mamat Hazry, Desa Feature extraction Ellipse fitness function Genetic algorithm Face emotion recognition Face emotion Detectors Recognition system Genetic algorithm (GA) Link to publisher's homepage at http://www.springerlink.com In this article, two subjects, one South East Asian (SEA) and the other Japanese, are considered for face emotion recognition using a genetic algorithm (GA). The parameters relating the face emotions in each case are entirely different. All six universally accepted emotions and one neutral are considered for each subject. Eyes and lips are usually considered as the features for recognizing emotions. This paper has two parts. The first part investigates a set of image processing methods suitable for recognizing face emotion. The acquired images have gone through a few preprocessing methods such as gray-scale, histogram equalization, and filtering. The edge detection has to be sufficiently successful even when the light intensity is uneven. So, to overcome this problem, the histogram-equalized image has been split into two regions of interest (ROI): the eye and lip regions. The two regions have been applied with the same preprocessing methods, but with different threshold values. It was found that the Sobel edge detection method performed very well in segmenting the image. Three feature extraction methods are considered, and their respective performances are compared. The method which is fastest in extracting eye features is adopted. The second part of the paper discusses the way to recognize emotions from eye features alone. Observation of various emotions of the two subjects lead to an unique eye characteristic, that is, the eye exhibits ellipses of different parameters in each emotion. The GA is adopted to optimize the ellipse characteristics of the eye features in each emotion based on an ellipse-based fitness function. This has shown successful emotion classifications, and a comparison is made on the emotions of each subject. 2009-08-06T12:28:02Z 2009-08-06T12:28:02Z 2007-08-10 Article Artificial Life and Robotics, vol.11 (2), 2007, pages 197-203. 1433-5298 (Print) 1614-7456 (Online) http://www.springerlink.com/content/5031051346335636/ http://hdl.handle.net/123456789/6688 en Springer Japan
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
Face emotion recognition
Face emotion
Detectors
Recognition system
Genetic algorithm (GA)
spellingShingle Feature extraction
Ellipse fitness function
Genetic algorithm
Face emotion recognition
Face emotion
Detectors
Recognition system
Genetic algorithm (GA)
Muthukaruppan, Karthigayan
Mohd Rizon, Mohamed Juhari
Ramachandran, Nagarajan
Masanori, Sugisaka
Sazali, Yaacob
Mohd Rozailan, Mamat
Hazry, Desa
Development of a personified face emotion recognition technique using fitness function
description Link to publisher's homepage at http://www.springerlink.com
format Article
author Muthukaruppan, Karthigayan
Mohd Rizon, Mohamed Juhari
Ramachandran, Nagarajan
Masanori, Sugisaka
Sazali, Yaacob
Mohd Rozailan, Mamat
Hazry, Desa
author_facet Muthukaruppan, Karthigayan
Mohd Rizon, Mohamed Juhari
Ramachandran, Nagarajan
Masanori, Sugisaka
Sazali, Yaacob
Mohd Rozailan, Mamat
Hazry, Desa
author_sort Muthukaruppan, Karthigayan
title Development of a personified face emotion recognition technique using fitness function
title_short Development of a personified face emotion recognition technique using fitness function
title_full Development of a personified face emotion recognition technique using fitness function
title_fullStr Development of a personified face emotion recognition technique using fitness function
title_full_unstemmed Development of a personified face emotion recognition technique using fitness function
title_sort development of a personified face emotion recognition technique using fitness function
publisher Springer Japan
publishDate 2009
url http://dspace.unimap.edu.my/xmlui/handle/123456789/6688
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score 13.222552