Intelligent Analysis Of Learning Status In Video Online Learning

With the rapid development of Internet technology,in every family,online shopping,online movie viewing and other scenes that once only appeared in science fiction have become a reality,and online education has become the focus of the times in recent years.Compared with traditional education,online education has many unique advantages,such as rich resources,timely update and small site restrictions.However,there are some disadvantages in the course learning through online education.For example,in the face of computer learning,the learning state of students is often lack of supervision.Based on this feature,it will be very valuable to realize the system of intelligent analysis of students'learning state.This thesis proposes a method of fatigue detection for students combined with facial feature information,and realizes the intelligent analysis and detection system of learning state.The system can obtain and analyze the facial feature information of students,and prompt when students are in fatigue state.The main research contents are as follows:(1)This thesis proposes a method to detect eye features in online education.In the process of detecting whether the eyes are open or closed,the least square method and other filtering rules are used for optimization.At the same time,using prior knowledge to locate the mouth position,and then using integral projection method to achieve feature detection.(2)A detection method of line of sight shift is proposed.On the basis of the existing methods,the vision shift caused by fatigue of the trainees was detected.This paper analyzes several algorithms of line of sight detection.According to the scene of home online education,we choose to detect the shift of line of sight by calculating the position relationship between pupil and eye contour.(3)A learning state intelligent analysis and detection system is designed and implemented.Through the related algorithms,face detection,closed state detection,vision shift detection and yawn state detection are carried out respectively.The fatigue state results are obtained by collecting the above facial feature information,and the detection results are fed back immediately to prompt the students.The experimental results show that the fatigue state detection method in this paper has a good detection effect for the fatigue state that students often appear,such as sleepiness,wandering,and vision dullness.The accuracy of the prompts is high,and it has the value of practical application.