Concentration grading method and system based on human eye action characteristics

Abstract

The invention discloses a concentration grading method and system based on human eye action characteristics. The method comprises the following steps: recording video data to be tested; extracting left-eye video data, right-eye video data, blinking duration and blinking frequency of the user according to the to-be-detected video data to obtain eye action features of the user; inputting the user eye action features into a pre-trained classification network to obtain the number of blinking times of the user in a concentrated state and the number of blinking times of the user in a non-concentrated state; and judging the concentration level of the user according to the ratio of the blinking times of the user in the concentration state to the blinking times of the user in the non-concentration state. The system comprises a data acquisition module, a feature extraction module, a classification module and a grading module. By using the system and the method, the concentration degree of the student in the online class can be analyzed, so that the learning quality of the student is improved. The concentration grading method and system based on the human eye action characteristics can be widely applied to the field of video processing.

Description

technical field [0001] The invention relates to the field of video processing, in particular to a method and system for grading concentration based on human eye movement characteristics. Background technique [0002] With the popularization and development of Internet technology, the distance network learning method is becoming more and more mature. Due to the particularity of the form, network distance education enables learners and lecturers to break the constraints of time and space. At present, the application field of network distance education is gradually expanding, which provides a good resource platform for our modern education, and students can complete the teaching plan even if they cannot return to school. However, various problems have gradually appeared in the widely used network distance education. Due to the limitation of time and space, the students and the teachers in the online class cannot communicate in real time, which leads to the phenomenon of fatigue...

AI Technical Summary

Problems solved by technology

However, various problems have gradually appeared in the widely used network distance education. Due to the limitation of time and space, the students and the teachers in the online class cannot communicate in real time, which leads to the phenomenon of fatigue and boredom when the students face the computer screen for a long time, which leads to the failure of learning. The decrease of concentration will affect the teaching effect of teachers and the quality of students' learning. At present, there is no relatively complete identification method of concentration

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