Student attendance based on face detection and recognition with PCA Algorithm using LattePanda

Abstract

Face is the representation of one’s identity. The human face is a complicated multidimensional visual model. Hence, it is very difficult to develop a computational model for recognizing it. Face Recognition, as it is often referred to, analyses characteristics of a person's face image input through a camera. Verification or identification can be accomplished from the distance of two-feet-away or more, without requiring the user to wait for long periods of time. Face recognition is widely used in many applications, such as security system. Traditionally, students’ attendance is taken manually by using attendance sheet, given by the faculty member in class. The paper describes how to take students’ attendance using face recognition. The face recognition is implemented with the help of Principal Component Analysis (PCA) algorithm. It recognizes the face of students and saves the response in database automatically. The system also includes the feature of retrieving the list of students who are absent in a particular day. LattePanda is used for image processing using OpenCV.