@inproceedings{03d784678ef14d62bb61d28cb9ab3265,
title = "Facial expression recognition based on 2D Gabor transforms and SVM",
abstract = "In the facial expression recognition, a dimension disaster will arise when taking the coefficient of Gabor transforms as the expression eigenvectors. To avoid this issue we draw grids on facial region, making the mean coefficient value of Gabor transforms of each gird as the eigenvectors. Furthermore we classify the expression by constructing the multi-class C-SVC, improved the accuracy and speed of the algorithm by dropping the redundant features using sequential backward selection. The experimental result proves the superiority of the algorithm we proposed to other algorithms.",
keywords = "2D Gabor transforms, C-SVC, Facial expression recognition, Feature extraction",
author = "Liu Chunhui and Zhao Zheng and Gao Feng",
year = "2011",
doi = "10.4028/www.scientific.net/AMM.58-60.238",
language = "英语",
isbn = "9783037851494",
series = "Applied Mechanics and Materials",
pages = "238--242",
booktitle = "Information Technology for Manufacturing Systems II",
note = "2011 International Conference on Information Technology for Manufacturing Systems, ITMS 2011 ; Conference date: 07-05-2011 Through 08-05-2011",
}