Research And Development Of Facial Expression Recognition System In Learning Environment

E-Learning, with its pervasiveness and convenience, has become more and more popular. At meantime, research achievement in areas such as pattern recognition and artificial intelligence have been more and more applied in E-Learning, such as laser pen system, attention detection system, voice recognition system, facial expression recognition system and so on. These intelligent systems, not only promote the development of E-Learning, but also bring better learning experiences to learners.This thesis introduces the application of facial expression recognition system in E-Learning environment. The main work includes: 1. Recognized key facial parts(eyes, mouth) and extracted their LBP features. 2. Analyzed the relationship between key parts(like eyes and mouth) of the facial expressions and the emotion states of students in learning environment. 3. Classified students'emotion states with SVM, after using PCA to reduce the dimensions an redundancy of the 2322 dimensions of LBP features of key facial parts. The average recognition rate of cross verification was above 90 percent. 4. Developed a facial expression recognition system to recognize emotion states of students in real-time. Finally, this thesis discussed the shortcomings and possible improvements of the system, providing a reference for future research.