Development of a personified face emotion recognition technique using fitness function
Link to publisher's homepage at http://www.springerlink.com
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer Japan
2009
|
| Subjects: | |
| Online Access: | http://dspace.unimap.edu.my/xmlui/handle/123456789/6688 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Malaysia Perlis |
| Language: | English |
| id |
my.unimap-6688 |
|---|---|
| record_format |
dspace |
| 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 |
| _version_ |
1643788577830600704 |