Face recognition and tracking for examination monitoring (digital invigilator)
In this paper, we propose a system for monitoring students in examinations. Here we use a camera for recognizing and tracking each student, each student we are pre allocated to a particular seat if the student goes beyond this point human invigilator will be alerted, and also faced tracking can be used for detecting any malpractice by any student. Here the camera is mounted on a servo motor to avoid any blind spots. The whole system can be designed and implemented around a raspberry pi embedded computer, this eliminates the use of a PC for running a face recognition program. Here for face detection and recognition python opencv can be used, in which Haar cascade classifier is used for detecting face and Fisher face recognizer is used for face recognition. Servomotor control will be based on the feedback from the camera.
- Manual invigilation
This system is designed for monitoring students during examinations. This system consists of a raspberry pi for central processing and controlling and a camera mounted on a servo motor. Camera is used for monitoring students through face detection and recognition. Python programming is used for image processing. An alert system can be added to raspberry pi, both local and remote alerts can be added. The local alert can be an alarm system and the remote alert can be an IoT-based message alert system.
Block diagram description:
- Raspberry is the central unit it runs the main code for the project
- The camera is interfaced to the raspberry pi through the USB interface
- Python programming is used for accessing the camera for video capture
- A servomotor is used for rotating the camera to a particular angle
- Servo is interfaced to the raspberry pi through a GPIO pin
- Here PWM is used for accurate controlling of servo
 Jiangyin Huang, Jing Zhao, “Identification of multi-model LPV model
with two scheduling variables using transition test,” Int. J. of
Modeling, Identification, and Control, 2018 Vol.29, No.1, pp.31 – 43.
 Wesam Jasim, Dongbing Gu, “Robust path tracking control for
quadrotors with experimental validation,” Int. J. of Modelling,
Identification and Control, 2018 Vol.29, No.1, pp.1 – 13.
 Ravi Kumar Mandava, Pandu Ranga Vundavilli, “Whole-body motion
generation of 18-DOF biped robot on a flat surface during SSP & DSP,”
Int. J. of Modelling, Identification, and Control, 2018 Vol.29, No.3,
pp.266 – 277.
 Rida Mezghache, Fadila Atil, “A template for formalizing reliable
Acme-based software architecture,” Int. J. of Computer Applications in
Technology, 2018 Vol.57, No.1, pp.14 – 27.
 G. O. Young, “Synthetic structure of industrial plastics (Book style
with paper title and editor),” in Plastics, 2nd ed. vol. 3, J. Peters, Ed.
New York: McGraw-Hill, 1964, pp. 15–64.
There are no reviews yet.