Abstract:

In the continuous development in field of science and technology, One of the most important AI approaches, computer vision is used in a wide range of fields. Computer vision involves the development of algorithms and techniques that enable computers to process and analyze images and videos to recognize objects, patterns, and other visual data. Computer vision techniques help computers to sight and understand content of digital images. Facial Recognition is an area where computer vision technology is used. It is the most intensely studied area in computer vision more than five decades. It has many applications like Automated Surveillance Systems, Security Monitoring System, Finding of Missing Person and Victim Identification and so on. In these days, it is mostly used for marking attendance of students and employees in colleges and organizations. smart attendance systems are valuable tools for organizations looking to improve attendance management, reduce administrative workload, and increase efficiency. This research of several machine learning techniques like Convolutional Neural Network, Support Vector Machine, Principal Component Analysis, Eigen face, Fisher face etc, many of which have been employed by other writers in Smart Attendance System (SAS) employing Facial Recognition, is extensive.

Description:

PCA (Principal Component Analysis), SVM (Support Vector Machine), CNN (Convolutional Neural Network), Haar Cascade, Local Binary Pattern, Eigen face, Fisher face