Human Face Detection and Facial Expression Identification

For interactive human and computer interface (HCI) it is important that the computer understand facial expressions of human. With HCI the gap between computers and humans will reduce. The computers can interact in more appropriate way with humans by judging their expressions. There are various techniques for facial expression recognition which focuses on getting good results of human expressions. Most of these works are done on standard databases of foreign origin with six (Neutral, Happy, fear, Anger, Surprise, Sad) basic expression identification. We propose Zernike moments based feature extraction method with support vector machine to identify 8 expressions (including Disgust, and Contempt) on JAFFE and Radboud faces database with discriminative multi-manifold analysis technique with Single Sample Per person (SSPP) and finally compared results of Zernike with Hu moments.