Combination of Facial Recognition and Interaction with Academic Portal in Automatic Attendance System

Son, Ngo Tung; Phuong, Le; Dinh, Tran Van

doi:10.1145/3316615.3316638

Cited by 5 publications

(7 citation statements)

References 20 publications

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“…It is possible to apply FR technology for automatic attendance taking at schools. There are several benefits from attendance considering using the existing camera system, such as save time and effort, provide striking evidence for quality assurance and human resource management tasks, avoid intermediary of infectious diseases [2]. The existing attendance taking system that uses fingerprint recognition is facing several challenges due to large intra-class variability and substantial inter-class similarity mentioned by Dyre and Sumathi [3].…”

Section: Problem and Motivationmentioning

confidence: 99%

“…The existing attendance taking system that uses fingerprint recognition is facing several challenges due to large intra-class variability and substantial inter-class similarity mentioned by Dyre and Sumathi [3]. Ngo et al combined the data from the academic portal with different FR techniques for the task of taking attendance in the classroom [2]. The result shows that their system works smoothly.…”

Section: Problem and Motivationmentioning

confidence: 99%

“…The universal approaches of classification algorithms, one-versus-all, all-versus-all (alternative of one-all-all) can all be severe with a large number of labels [18]. As mentioned in the previous section Ngo and colleagues proposed to narrow the scope of classification problems by using multiple classifiers, each of which will be used only for a specific group of students based on their class schedule [2]. Their contributions inspire our research.…”

Section: Related Workmentioning

confidence: 99%

“…In this study, we provide an empirical comparison of the latest FR libs as well as classification algorithms through our dataset in our real environment project. Ngo et al also conducted a review on libraries, but the reviewed facial embedding libs were out of date [2]. The remainder of the paper is organized as follows: Section 2 describes the architectural design of the system.…”

Section: Contribution Of This Papermentioning

confidence: 99%

See 3 more Smart Citations

Implementing CCTV-Based Attendance Taking Support System Using Deep Face Recognition: A Case Study at FPT Polytechnic College

et al. 2020

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Face recognition (FR) has received considerable attention in the field of security, especially in the use of closed-circuit television (CCTV) cameras in security monitoring. Although significant advances in the field of computer vision are made, advanced face recognition systems provide satisfactory performance only in controlled conditions. They deteriorate significantly in the face of real-world scenarios such as lighting conditions, motion blur, camera resolution, etc. This article shows how we design, implement, and conduct the empirical comparisons of machine learning open libraries in building attendance taking (AT) support systems using indoor security cameras called ATSS. Our trial system was deployed to record the appearances of 120 students in five classes who study on the third floor of FPT Polytechnic College building. Our design allows for flexible system scaling, and it is not only usable for a school but a generic attendance system with CCTV. The measurement results show that the accuracy is suitable for many different environments.

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Section: Problem and Motivationmentioning

confidence: 99%

Section: Problem and Motivationmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Contribution Of This Papermentioning

confidence: 99%

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Implementing CCTV-Based Attendance Taking Support System Using Deep Face Recognition: A Case Study at FPT Polytechnic College

et al. 2020

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“…The student behavior monitoring system is directly connected to the camera network and academic portal to retrieve the detailed schedule and reduce the scale of the student recognition, very similarly to Ngo et al because their system also takes automatic attendance [17]. It only retrieves data from these systems, and does not modify or interfere.…”

Section: System Overviewmentioning

confidence: 99%

A Computer-Vision Based Application for Student Behavior Monitoring in Classroom

et al. 2019

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Automated learning analytics is becoming an essential topic in the educational area, which needs effective systems to monitor the learning process and provides feedback to the teacher. Recent advances in visual sensors and computer vision methods enable automated monitoring of behavior and affective states of learners at different levels, from university to pre-school. The objective of this research was to build an automatic system that allowed the faculties to capture and make a summary of student behaviors in the classroom as a part of data acquisition for the decision making process. The system records the entire session and identifies when the students pay attention in the classroom, and then reports to the facilities. Our design and experiments show that our system is more flexible and more accurate than previously published work.

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A Review to Enhance Operations in an Airport with a Deep Learning and Computer Vision Approach

Kumaar

Malavika

Monisha

et al. 2022

Advances in Intelligent Systems and Computing

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Combination of Facial Recognition and Interaction with Academic Portal in Automatic Attendance System

Cited by 5 publications

References 20 publications

Implementing CCTV-Based Attendance Taking Support System Using Deep Face Recognition: A Case Study at FPT Polytechnic College

Implementing CCTV-Based Attendance Taking Support System Using Deep Face Recognition: A Case Study at FPT Polytechnic College

A Computer-Vision Based Application for Student Behavior Monitoring in Classroom

A Review to Enhance Operations in an Airport with a Deep Learning and Computer Vision Approach

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