期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2012
卷号：9
期号：6
出版社：IJCSI Press
摘要：Facial Expression Recognition is rapidly becoming area of interest in computer science and human computer interaction because the most expressive way of displaying the emotions by human is through the facial expressions. In this paper, recognition of facial expression is studied with the help of several properties associated with the face itself. As facial expression changes, the curvatures on the face and properties of the objects such as, eyebrows, nose, lips and mouth area changes. We have used Affine Moment Invariants to compute these changes and computed results (changes) are recorded as feature vectors. We have introduced a method for facial expression recognition using Affine Moment Invariants as features. We have used Artificial Neural Network as a classification tool and we developed associated scheme. The Generalized Feed-forward Neural Network recognizes six universal expressions i.e. anger, disgust, fear, happy, sad, and surprise as well as seventh one neutral. The Neural Network trained and tested by using Scaled Conjugate Gradient Backpropogation Algorithm. As a result we got 93.8% classification rate.
关键词：Artificial Neural Network; Facial Expressions; Affine Moment Invariants; Human computer Interaction
