Emotion Basic action using Face Recognition and Detection ANN

Abstract

Face detection and recognition are the popular research area in the field of security vision and authentication because it is the first step in many applications like intelligence weapon with sensors and surveillance. Face detection and recognition algorithms are computationally intensive, which is challenging to prove face detection applications in real-time. Moreover, authentication of many security areas is a significant issue in the world of control, electronic, and communication. Face recognition is a secessionist of biometric verification and has been widely used at door control systems, video conference monitoring, weapons control systems, and network security, and so on. Face detection is used as a part of a facial recognition system by the author. Its technologies consist of the humancomputer interface, face database management system, video surveillance, and human behavior monitoring system. This paper is achieving face detection and recognition that will integrate with robot mouth emotional technology using database systems. The system will have a database of registered peoples. If the face matches the database, then it displays the friends, enemies, awesome things, annoys, and the robot mouth will be an emotion system. These six motors' emotion systems stilled testing by using outputs of computer programs or microcontroller systems.

A YOLOv3 Inference Approach for Student Attendance Face Recognition System

“…The research also includes three different mobile applications that enable parents, students, and teachers to control and conduct the attendance process in real time on their smartphones. A similar study carried out by [9] for face recognition, the system was developed by combining universal components to construct a portable device to monitor student attendance.…”

“…In recent trends in modern industries, automated attendance system has been anticipated by using several identification strategies like biometric recognitions such as palm vein [3], [4], fingerprint [5], [6], and face recognition [7], [9] to recognized and mark the students as present. The other proposed systems for tracking attendance used RFID [10], [11], barcode [12], QR code [13], mobile devices that uses Near Field Communication (NFC) [14], and some systems developed in a portable device like smartphone [15].…”