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It is an important direction increasing emotional recognition in the network system. This paper uses the improved Adaboost algorithm based on front-end color optimization to detect face and locate eye and mouth positions, adopts the deformable template matching method to extract eye spacing and uses the method based on lip color model to extract mouth radian. These methods have good test results....
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...
The traditional intelligence network tutoring system can not be implemented affective tutoring. This paper proposed that it can obtain the chief facial features to analyze learners' emotion, through the face detection and location under the web environment. It is based on the skin module to locate a human face to obtain the area of the face and it is based on the apriori knowledge and the best segmentation...
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