Intelligent video teaching method and system for realizing action recognition

By monitoring learners' body and facial states in real time and dynamically adjusting the video playback progress and content, the problems of personalization and fatigue relief in intelligent video teaching are solved, enabling autonomous updates and efficient learning.

CN114581835BActive Publication Date: 2026-02-06SHANDONG UNIV
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Patent Information

Application Number
CN202210240218.9
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2022-03-10
Publication Date
2026-02-06
Estimated Expiration
2042-03-10

AI Technical Summary

Technical Problem

Existing intelligent video teaching methods struggle to provide personalized, adaptive learning content, cannot autonomously update video playback content, and are ineffective in alleviating student fatigue.

Method used

By acquiring learners' historical learning information, monitoring learners' body movements and facial states in real time, and using RGB-D cameras and facial recognition technology, the video playback progress and content are dynamically adjusted, and learning interaction is carried out by combining walking and action interaction methods.

Benefits of technology

It enables autonomous updates and personalized adjustments to video playback content, alleviating student fatigue, improving learning efficiency, adapting to individual differences and needs of different learners, and building a learning model that everyone can learn, learn anywhere, and learn anytime.

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Abstract

The application provides an intelligent video teaching method and system for action recognition, comprising: obtaining historical learning information of a learner; obtaining and playing a learning video based on the historical learning information of the learner; wherein, in the process of playing the learning video, the position of a body joint of the learner is obtained in real time, the body action of the learner is judged, the playing progress of the learning video is controlled based on the body action of the learner; meanwhile, a face color image of the learner is obtained, the face key points in the face color image are identified based on the face color image of the learner, the mean value of left and right eye closure and the mouth opening angle are calculated based on the face key points, the head rotation angle is calculated based on the face color image, and the video playing content is updated based on the mean value of left and right eye closure, the mouth opening angle and the head rotation angle. The body control of the playing progress and the autonomous update of the playing content in online education are realized.
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