Research And Application Of Student's Attention Recognition In E-Learning System

With the rapid development of information technology,the e-Learning system was proposed,and it obtains the promotion rapidly in the world. E-learning has realized the superiority which face-to-face in the teaching is unable to manifest, it might erase the barrier of the space,the time, the eliminates person's age , the physical condition, the individual to accept ability difference and so on the traditional teaching the unevadable certain barriers, it makes any learner may, at any place, any time to learn any thing.The convenient, fast, economical and nimble way of teaching is affecting the modern education more and more profoundly. Although the traditional e-Learning system has realized the long-distance independent study, but cannot solve the problem of emotion communication between the teachers and students in the learning process, and cannot achieve the goal of the teaching through emotion.The effect of learning is not very good.The emotion communication in the teaching process is very important.It is most should not neglect. Artificial emotion and the development of pattern recognition to solve the problem of which lack the emotional lay the theoretical and technical foundation.The learner facing the indifferent non-expression's screen for long time,will produce fatigue, feelings of resentment. The modern e-Learning in which adding emotion recognition of the learners to capture and identify emotions ,can adjust the strategy of teaching, and may serve well the independent study.Based on the research of the camera control, face and eye detection and localization, attention detection, A means of attention identification based on AdaBoost algorithm is proposed. It detects directly the state of human eyes The major work includes:1.The algorithm selection: This article compares some typical face detection algorithm. Is to be achieved in view of real-time face detection, AdaBoost algorithm on a detailed analysis. AdaBoost algorithm chosen as the attention and recognition of face detection and eye localization algorithm module.2.Implementation process: Through the camera get learners face images, its for face recognition, based on the students in this type of judge of three emotions that normal learning status, leave status, sleepy state. Using VC + +6.0 and OpenCV the attention of students is identified. Emotion recognition use static image analysis system to capture the form used in the implementation. Set the appropriate shutter speed. With a certain interval of time to detect the presence or absence of face and the availability of the human eye, to judge learner status, and implement appropriate measures.