Mahalanobis distance based facial expression recognition
Kong Lingwang · Journal of Lanzhou University · 2005
It was proposed that Mahalanobis distance based technique could classify four facial expressions namely: neutral, joyful, surprised and sad. First we've mapped all the sample vectors to a new coordinate by using the optimal linear transform matrix W that makes Fisher criterion function maximum. Then in this new coordinate we calculated the Mahalanobis distance of every sample vector to the mean vectors of the four classes and classified it to the class to which its Mahalanobis distance is the least, and the average recognition rate we've got is 80.25%.