HOG and Cloud Computing based Face Recognition for Attendance Monitoring
V Sudha, R. Kalaiselvi, C K Jithenthiriya · 2023
Participation plays a key role in the classroom culture. When calling out the students' names at the beginning and end of a lecture, lecturers may miss a student, or someone may respond several times to substitute their peers. Face identification can be difficult when using low-definition video and other information systems with the assistance of facial recognition technologies. This necessitates the need to develop a novel device to quickly and accurately identify human faces from images and videos. Many algorithms and techniques have been recently developed to improve the facial recognition accuracy. Deep learning has been recently implemented in various real-time applications to identify and perceive multiple faces at the same time. When it comes to computers, however, it is unrealistic to attempt any of the human identity. The identification of the human identity is a critical aspect of biometrics. The biometric results are consistent with human characteristics. Remote and applied facial expressions can be used to enhance the results. Computers that identify and recognize faces can be used for a variety of purposes, including criminal recognition, network surveillance, biometric authentication, and so on. In this paper, an automated system for attendance recognition is proposed.