Article Details

Abstract

The traditional attendance methods in colleges and universities, such as roll call, RFID card, and so on, exist problems such as low efficiency, easy to sign on behalf, missing signature. Most of the existing face attendance systems use student terminal devices to participate in attendance activities, although the accuracy of identity verification is improved, but it is impossible to confirm whether it is carried out under the specified scenarios, causing inconvenience to teachers and students. In view of this, an intelligent class attendance system in colleges and universities based on InsightFace algorithm is adopted. The face information of each student is captured through multiple groups of face image acquisition terminals arranged in the specific position of the attendance situation, and centrally recognized and processed on the cloud server. The system quickly and accurately realizes the attendance record and effectively reduces the wrong signature, missing signature, signing on behalf and other behaviors. At the same time, the use of this system does not require teachers and students to make extra work on attendance, so as to improve classroom efficiency.

Keywords

InsightFace; Embedded Artificial Intelligence; end-cloud collaboration; face recognition; intelligent attendance

References

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About the authors

Hu Xiuqi (2005-), female, Han ethnicity, from Zaozhuang, Shandong Province, is currently pursuing a bachelor's degree with research interests in embedded systems and image processing.