In today’s academic system, proper student attendance management is crucial for the academic institutions to disseminate and give quality education and success to students. Managing the attendance of each student can be a great burden on the teachers if they do it manually. The traditional methods practiced in most of the institutions include calling names of students or signing on papers, which are highly time-consuming and insecure methods. To overcome these problems, a smart and auto attendance management system may be developed. Earlier, several automated attendance systems have been proposed based on biometric recognition, barcode, near field communication mobile devices like Bluetooth module attendance system and QR code. However, all these systems are not efficient in terms of processing time, cost, and accuracy. Face recognition is one of the biometric methods to improve this system. The purpose of this work is to survey several algorithms, their benefits, and their drawbacks. We also go over the steps followed in the facial recognition process. This review will be beneficial for upcoming researchers for selection of appropriate techniques for face recognition.

Keywords : Machine Learning (ML), Logistic Regression (LR), Support Vector Machine (SVM), K nearest neighbour (KNN), Random Forest (RF), Principal Component Analysis (PCA), Convolutional Neural Network (CNN).