Intelligent Face Recognition based attendance system

Abstract

Student consistent performance is a challenge for educational institutions worldwide, especially in India. Inadequate attendance is one of the prime reasons that is often correlated with this drop in student performance. The method generally employed in academic institutions to register attendance is the manual record method by either signing or calling out the pupil's name. This takes a long time and is inefficient, e.g., missing out on names and proxy attendances. Professors are increasingly relying on a computer-based student attendance verification system to help them keep track of attendance. Our project deploys a facial recognition-based attendance system. Automated facial recognition systems have made tremendous improvements in today's environment. We found out that Real-Time Face Recognition is an appropriate system for recording and tracking daily attendance. This type of attendance system involves recording the attendance using high-definition (HD) monitor video and related technologies for facial recognition of students. Our facial recognition system does this by analyzing the image captured by the security cameras. Although we employed a range of algorithms and software to achieve this, the primary concept to be used here is Deep Learning. It facilitates the conversion of video frames to photographs, allowing the student's face to be easily recognized for attendance purposes and the attendance database to be automatically updated.