Automatic Attendance System based on FaceRecognition using Machine Learning

Abstract

Advancements have been made in the field of face recognition technology. Controlling aperson's attendance in real time via facial recognition technology. Face recognition is the process of recognizing a person by their facial characteristics. Various computer vision algorithms, including those used for face detection, expression recognition, and video surveillance, can make use of a person's unique facial features. A face detection and recognition- based attendance monitoring system might very well rapidly and accurately locate and identify people in photographs or video footage. In addition to being laborious to maintain, the time-honored practice of physically ticking off attendees is inefficient. This research work presents the working of a cascade classifier built with machine learning to improve the face detection results. This has been done by comparing the face images in the current image to a database of previously trained faces. The acquired image contributions are searchedfor a previously registered face, and once found, the person's attendance is recorded automatically.