Open AccessResearch on Campus Attendance System Based on Face Recognition and Trajectory Tracking
Author(s) -
Fengping Cao,
Lin Zhu
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/769/4/042065
Subject(s) - attendance , computer science , tracking (education) , trajectory , facial recognition system , multimedia , medical education , artificial intelligence , psychology , medicine , political science , feature extraction , pedagogy , physics , astronomy , law
The traditional Morning jog attendance in colleges and universities is limited to manual supervision by swiping card attendance, which is prone to queuing and sign-in on behalf of others. In addition, the lack of quantitative records of exercise data makes supervision difficult. Location-based attendance systems represented by Dingding time attendance, or simple face recognition attendance systems cannot achieve accurate attendance. The campus happy running system based on face recognition and trajectory tracking innovatively combines face recognition and trajectory tracking, and students achieve accurate attendance certification within the designated “geo-fence”. Practice shows that the system can meet the special needs of colleges and universities for Morning jog attendance and data recording, and it effectively improves the accuracy of identity verification.