Attendance System Implementation Using Real Time Face Recognition
Priyanka Tyagi, Mayank Kaushik, Harshit Kumar Singh, Nikhil Jaiswal · 2021
In this paper, we propose Facial Recognition using Supervised Learning technique to implement an attendance system using a comparative study between different methods of face detection and face recognition. The first step that is required is face detection, i.e., detecting faces in an image, video or real time coverage consisting of different types of objects (distinguishing faces from non-faces). Once the face is detected, feature extraction, i.e., determining the uniqueness of the face by takin out the features is performed. Eventually, training and classification of the facial databases is done and is tested using various classification techniques based on the comparative performance and efficiency for recognizing faces. We attempt to use this facial recognition system on a data set of faces of institute/university students for which the attendance system will be implemented. Attentiveness Monitoring feature is added which monitors facial features such as eye blinks, yawn and eye movements, to determine the relative attentiveness among students. Consolidated attendance is easily available to view and download.