Facial Expression Classification using Gabor and Log-Gabor Filters

Authors:
Nectarios Rose
Affiliations:
Victoria University of Technology, Australia
Venue:
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Year:
2006

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Abstract

Facial expression classification has achieved good results in the past using manually extracted facial points convolved with Gabor filters. In this paper, classification performance was tested on feature vectors composed of facial points convolved with Gabor and Log-Gabor filters, as well as with whole image pixel representation of static facial images. Principal Component Analysis was performed on these feature vectors, and classification accuracies compared using Linear Discriminant Analysis. Experiments carried out on two databases show comparable performance between Gabor and Log-Gabor filters, with a classification accuracy of around 85%. This was achieved on low-resolution images, without the need to precisely locate facial points on each face image.