Facial Expression Recognition Based on 2D Gabor Transforms and SVM

Abstract:

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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.

Info:

Periodical:

Edited by:

Qi Luo

Pages:

238-242

DOI:

10.4028/www.scientific.net/AMM.58-60.238

Citation:

C. H. Liu et al., "Facial Expression Recognition Based on 2D Gabor Transforms and SVM", Applied Mechanics and Materials, Vols. 58-60, pp. 238-242, 2011

Online since:

June 2011

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Price:

$35.00

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