An automatic attendance system for elementary and middle school classrooms based on monitoring image seat discrimination

Abstract

The invention discloses an automatic attendance system for classrooms of primary and secondary schools based on monitoring image seat discrimination, comprising: a monitoring camera, a video server, an attendance server and various attendance record viewing terminals. The system makes full use of the characteristics of relatively fixed classroom seats in primary and secondary schools. It only needs a pair of low-resolution classroom panoramic images to quickly complete a attendance check for the classroom, and the attendance accuracy rate is high. Save students' biometric information, no risk of personal privacy leakage, and low requirements for hardware system performance.

Description

technical field [0001] The invention belongs to the technical field of optical network communication, and more specifically relates to an automatic class attendance system for middle and primary schools based on monitoring image seat discrimination. Background technique [0002] Due to their relatively young age, poor self-discipline ability, and easy to be affected by external factors, primary and middle school students will voluntarily skip classes or be passively victimized. Most primary and secondary schools have formulated strict classroom attendance systems for the purpose of protecting students and maintaining the normal classroom teaching order of the school. [0003] The traditional attendance method counts and absents students through classroom roll call or teacher's visual inspection. Due to the large number of people, this method will consume a lot of time and energy for teachers and students, the efficiency of attendance is low, and it is impossible to carry ou...

AI Technical Summary

Problems solved by technology

However, this method still needs to collect, extract, and store student face feature information in advance, and it is difficult to realize the technology of capturing and recognizing students' faces in class. The recognition process is easily affected by factors such as changes in student posture and expression. Complex, low recognition rate

At the same time, the performance requirements of hardware equipment are extremely high, and a surveillance camera with high resolution and high frame rate is required to clearly capture the facial features of each student in the classroom. Therefore, it cannot be applied in a short time

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