EXPRESSION INTENSITY MEASUREMENT FROM FACIAL IMAGES BY SELF ORGANIZING MAPS
Facial expression recognition and inferring emotion from an expression is a challenging task. Many methods have been proposed to recognize facial expressions, but the more challenging task facial expression intensity classification remains less focused. Here we propose a system that is able to provide an estimation of facial expression intensity from facial images. At first each image of these sequences are normalized and cropped based on a fixed template. Then, features are captured from Gabor wavelet transformation of these images followed by Principle Component Analysis (PCA). Finally, Self Organizing Maps (SOM) are applied to determine the intensity of emotion from these principle components. In this work we propose a heuristic; MDC (minimum distance criterion) that is able to provide a quantitative measurement about the goodness of a combination of PCs from the intensity measurement point of view. Moreover, we propose a method to represent the results of SOM in the form of membership functions to visualize the qualitative performance.
Facial ezpression emotional intensity Gabor PCA SOM
ASHRAFUL AMIN HONG VAN
Department of Electronic Engineering, City University of Hong Kong, Hong Kong Department of Electronic Engineering, City University of Hong Kong, Hong Kong School of Electrical &
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
3490-3496
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）