Paper Info
Title
Facial expression features extraction based on Gabor wavelet transformation
Abstract
Features extraction is a key step in facial expression recognition system. In order to extract facial expression features that are subject-independent and robust to illumination variety, this paper introduces a facial expression features extraction algorithm. Given a still image containing facial expression information, preprocessors are executed firstly, which include expression sub-regions segmentation, grayscale and scale normalization. Secondly, expression feature vectors of the expression sub-regions are extracted by Gabor wavelet transformation to form elastic graph for expression. Finally, the features of six basic expressions shown by different subjects under different illumination conditions are extracted and compared each other. The experimental results show that expression features can be extracted effectively based on Gabor wavelet transformation, which is insensitive to illumination variety and individual difference.
Year
DOI
Venue
2004
null
Jisuanji Gongcheng/Computer Engineering
Keywords
Field
DocType
still image,gabor wavelet transformation,scale normalization,pattern recognition,wavelet transforms,facial expression recognition system,expression subregions segmentation,elastic graph,expression feature extraction,emotion recognition,feature extraction,facial expression features extraction,grayscale normalization,feature vector,luminance,preprocessor,facies,illumination,graph transformation,gray scale,gabor wavelets,facial expression,segmentation
Computer vision,Expression Feature,Expression (mathematics),Pattern recognition,Gabor wavelet,Computer science,Feature extraction,Gabor filter,Facial expression,Artificial intelligence,Grayscale,Wavelet transform
Conference
Volume
Issue
ISSN
31
15
null
ISBN
Citations 
PageRank 
0-7803-8566-7
6
0.50
References 
Authors
6
3
Name
Order
Citations
PageRank
Jingfu Ye160.50
Yongzhao Zhan234451.09
Shunlin Song381.93