Abstract
We propose a facial expression recognition method using several facial feature points associated with a majority of facial expressions. The facial feature points consist of the end points and centroids of eyebrows and eyes as well as several points around nose and mouth. We define a number of facial features based on the interrelation between some facial feature points including the distance between two facial feature points and the distribution of intensity values of the pixels in the region formed by three facial feature points. Since these facial features can be easily obtained from facial images with low computational cost, the proposed method performs efficient recognition. In addition, we propose a criterion to estimate the usefulness of facial features based on their variance ratio. By introducing feature extraction based on principal component analysis using only useful facial features, we develop an effective facial expression recognition method taking the tradeoff between recognition accuracy and recognition speed into consideration.
