The Application of Facial Characteristics Extraction in the Intelligent Network Teaching System

The traditional teaching of intelligent network system does not have the function of emotion teaching, so the paper has put forward an idea to obtain the chief facial features to analyze learners´ emotion. This paper bases the color front-optimized improved Adaboost face detection algorithm to detect human face, uses the best segmentation threshold value to obtain the eyelid spacing and the difference between the mouth color and other skin to detect the mouth. These methods have achieved good results. At the same time, the study provides the necessary premise to the realization of intelligent network teaching system emotional education.