Attendance Management Using Automatic Face Tracking System
Shruti Ramesh Babu1, Subhashree Navaneethan2, S. Prabakaran3
1Shruti Ramesh Babu, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Subhashree Navaneethan, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
3Dr. S. Prabakaran, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 25 May 2019 | Revised Manuscript received on 03 June 2019 | Manuscript Published on 22 June 2019 | PP: 61-62 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C10130283S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In present education system, attendance plays a significant role in performance, morale and productivity. The conventional methods are highly time consuming and subject to various kinds of errors. This paper presents an approach for efficient face tracking and matching for an automatic attendance monitoring system using technologies such as object detection, face recognition and convolutional neural networks.
Keywords: Object Detection, Convolutional Neural Networks, Face Recognition, Attendance Monitoring.
Scope of the Article: Wireless Multimedia Systems