Facial Expression Recognition Using Eigenspaces

A lot of information is conveyed by human beings in the form of facial expression apart from just what is spoken. Proper recognition of such expression has thus become important for any modern human computer interface. We present here a method of facial expression recognition based on Eigenfaces. It is a modified method from the original Eigenfaces approach [1] and starts out with the human vision as a standard reference point – by making use of the standard JAFFE database and computes the expression contained by the image of a test face. It is a unique approach which directly classifies a test image as belonging to one of the six standard expressions - anger, disgust, fear, happy, sad or surprise with great accuracy. In this paper, we present with experimental proof the accuracy of such a strategy with analysis and discussion on further ways to improve upon it.