Automated Attendance Tracker

Authors

  • Rohan Vasista Student, Department of Computer Science and Engineering, Alva's Institute of Engineering and Technology, Moodbidre, India
  • Sachin Rajora Student, Department of Computer Science and Engineering, Alva's Institute of Engineering and Technology, Moodbidre, India
  • Suman Rathod Student, Department of Computer Science and Engineering, Alva's Institute of Engineering and Technology, Moodbidre, India
  • C. Sahana Student, Department of Computer Science and Engineering, Alva's Institute of Engineering and Technology, Moodbidre, India
  • Reena Lobo Assistant Professor, Department of Computer Science and Engineering, Alva's Institute of Engineering and Technology, Moodbidre, India

Keywords:

Face recognition, Open-source Computer Vision, Multi cascade convolution neural networks

Abstract

From the most basic attendance systems to the most important security systems, tracking systems are in high demand nowadays. With the rapid advancement of AI and computer vision. These tracking systems have improved in accuracy and precision, leading in increased stability and durability. The suggested project is based on the detection, recognition, and tracking of images and videos. The appearance of the face with the help of the Camera and Open CV formula, facial recognition is enforced. The system will recognize a specific student's face and automatically save the response in information. The system also has the capability of retrieving a list of pupils who are absent on a specific day. The varied data is recorded with the help of a camera that is linked as part of the front of the classroom, which is capable of continuously filming pupils, detecting faces in images, distinguishing appearances with information, and recording attendance. This work begins with a review of related studies in the subject of participation administration as well as facial recognition. Our framework structure and plan are presented at that time. Finally, the experiments were implemented, demonstrating the advancement of the attendance system's performance. With the help of OpenCV, this work is used to find the face.

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Published

2021-07-18

How to Cite

[1]
R. Vasista, S. Rajora, S. Rathod, C. Sahana, and R. Lobo, “Automated Attendance Tracker”, IJRESM, vol. 4, no. 7, pp. 178–181, Jul. 2021.

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Articles