Learning, Emotional And Emotional Model Of Online Teaching Environment

With the increase of people's interest in the interface of human and machine, affective computing is becoming a research focus. If computers and robots could understand and deliver emotion just like human, the relation between human and machine would be changed radically, and then the computer could provide better service for people.Modern service industry has become an important driving force for economic growth, E-learning System is particularly innovative services, and has achieved a certain degree of development. People have paid more attentions to humanistic and intelligent instruction. Meanwhile, the research results of brain sciences indicate that emotion make important contribution to human learning. However, the current modem distance education system is lake of the emotional interaction between teachers and students. Based on the research of the artificial psychological and affective computing, the thesis will introduce the concept of affective computing into the network Teaching System, which can identify the learner's facial expressions, and analysis their studying states through the emotional cognitive model Based on fuzzy logic. In this paper, the main achievements are summarized as follows:1. Providing a thorough survey of the facial expression recognition and the emotional model commonly used at home and abroad after briefly introducing the basic emotion theory. According to the actual learning mood in the network environment, the thesis presents a method using approach-withdrawal and care to recognize learns' emotion state after the research of the emotion classification and the emotional dimensional theory, and constructs the two-dimensional space through the curve-fitting method.2. The research of face detection based on the skin-color and facial feature extraction. In the YUV skin-color model, much non-skin-color area can be wiped off according to the color density, facial candidate region can be gotten through the horizontal and vertical projection and the center of mouse and eye can be ascertained by morphological operations after image binarization.3. Presenting a novel emotion recognition model based on fuzzy Logic. Firstly, the student's emotions are considered to three types, and these types are described by two emotion characteristic as a vector. Secondly, the new method to pick-up the two emotion characteristic from the image sequences. Lastly, the membership function of each emotion characteristic is established and the appropriate judgment is done.4. Designing emotional reaction model. Emotional reaction is impacted by a number of factors, but three factors are considered here: the evaluation of learning content, the evaluation of online time and the current emotion. According to cognitive teaching theory, the emotion recognition model in the E-Learning is implemented in the VC 6.0 platform.