It is a challenging task to improve the real-time property and objectivity of the effect assessment for the distance education. This paper presents a QoE (Quality of Experience) assessment system based on the attention of online user. The system captures the video frames from two cameras periodically and synchronously, using the adaptive image binarization based on the linear average threshold for the pretreatment, then processing with edge detection and filtering in the cross-directions at the same time. System gets the position of computer screen and user eyeball. Analyzing the detection results comprehensively obtains the attention of online user by some judging conditions, and finally acquires the quality of user experience. Experimental results demonstrate the feasibility and efficiency
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