期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2012
卷号：2
期号：2
页码：391-394
出版社：International Journal of Soft Computing & Engineering
摘要：Facial Expression Recognition is rapidly becoming area of interest in computer science and human computer interaction. 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. Similarly, intensity of corresponding pixels of images also changes. We have used statistical parameters to compute these changes and computed results (changes) are recorded as feature vectors. Artificial neural network is used to classify these features in to six universal expressions such as anger, disgust, fear, happy, sad and surprise. Two-layered feed forward neural network is trained and tested using Scaled Conjugate Gradient back-propagation algorithm and we obtain 92.2 % recognition rate.
