Evaluation of Gabor-wavelet-based facial action unit recognition in image sequences of increasing complexity
Abstract
Previous work suggests that Gabor-wavelet-based methods can achieve high sensitivity and specificity for emotion-specified expressions (e.g., happy, sad) and single action units (AUs) of the Facial Action Coding System (FACS). This paper evaluates a Gabor-wavelet-based method to recognize AUs in image sequences of increasing complexity. A recognition rate of 83% is obtained for three single AUs when image sequences contain homogeneous subjects and are without observable head motion. The accuracy of AU recognition decreases to 32% when the number of AUs increases to nine and the image sequences consist of AU combinations, head motion, and non-homogeneous subjects. For comparison, an average recognition rate of 87.6% is achieved for the geometry-feature-based method. The best recognition is a rate of 92.7% obtained by combining Gabor wavelets and geometry features.
BibTeX
@conference{Tian-2002-8447,author = {Ying-Li Tian and Takeo Kanade and Jeffrey Cohn},
title = {Evaluation of Gabor-wavelet-based facial action unit recognition in image sequences of increasing complexity},
booktitle = {Proceedings of 5th IEEE International Conference on Automatic Face and Gesture Recognition (FG '02)},
year = {2002},
month = {May},
pages = {229 - 234},
}