Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru

Miguel Torres Vargas; Luis Fernando Rojas Valle; Diego Porras Vera; Daniel Gamarra Moreno

doi:10.1109/ICRCV59470.2023.10329180

Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru

Miguel Torres Vargas
, Luis Fernando Rojas Valle
, Diego Porras Vera
, Daniel Gamarra Moreno

Universidad Continental

Research output: Chapter in Book/Report › Conference contribution › peer-review

Abstract

Facial recognition systems on learning platforms like Moodle enable fast and efficient evaluation, automating the detection of impersonation in online exams. This project implements a Moodle plugin that performs facial recognition on the student attempting to take a quiz. It consists of two parts for authentication through a webcam: the first part occurs before accessing the quiz, and the second part involves surveillance through a camera during the quiz. The plugin was developed using the PHP and JavaScript programming languages, as well as Face-api. The JavaScript API detects and recognizes faces in the web browser using Tiny Yolo v2 and FaceRecognizerNet. It compares a student's photo or image with the image from their webcam while they are taking the quiz. The Moodle plugin achieved an average error probability of 39.39% for face detection similarity distance.

Original language	American English
Title of host publication	2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	164-168
Number of pages	5
ISBN (Electronic)	9798350326369
DOIs	https://doi.org/10.1109/ICRCV59470.2023.10329180
State	Indexed - 2023
Event	5th International Conference on Robotics and Computer Vision, ICRCV 2023 - Nanjing, China Duration: 15 Sep 2023 → 17 Sep 2023

Publication series

Name	2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023

Conference

Conference	5th International Conference on Robotics and Computer Vision, ICRCV 2023
Country/Territory	China
City	Nanjing
Period	15/09/23 → 17/09/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

face recognition
moodle
plugin

Access to Document

10.1109/ICRCV59470.2023.10329180

Cite this

Vargas, M. T., Valle, L. F. R., Vera, D. P., & Moreno, D. G. (2023). Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru. In 2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023 (pp. 164-168). (2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICRCV59470.2023.10329180

Vargas, Miguel Torres ; Valle, Luis Fernando Rojas ; Vera, Diego Porras et al. / Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru. 2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 164-168 (2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023).

@inproceedings{1860645b1c124ed68ca72d52d416ab7a,

title = "Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru",

abstract = "Facial recognition systems on learning platforms like Moodle enable fast and efficient evaluation, automating the detection of impersonation in online exams. This project implements a Moodle plugin that performs facial recognition on the student attempting to take a quiz. It consists of two parts for authentication through a webcam: the first part occurs before accessing the quiz, and the second part involves surveillance through a camera during the quiz. The plugin was developed using the PHP and JavaScript programming languages, as well as Face-api. The JavaScript API detects and recognizes faces in the web browser using Tiny Yolo v2 and FaceRecognizerNet. It compares a student's photo or image with the image from their webcam while they are taking the quiz. The Moodle plugin achieved an average error probability of 39.39\% for face detection similarity distance.",

keywords = "face recognition, moodle, plugin",

author = "Vargas, \{Miguel Torres\} and Valle, \{Luis Fernando Rojas\} and Vera, \{Diego Porras\} and Moreno, \{Daniel Gamarra\}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 5th International Conference on Robotics and Computer Vision, ICRCV 2023 ; Conference date: 15-09-2023 Through 17-09-2023",

year = "2023",

doi = "10.1109/ICRCV59470.2023.10329180",

language = "American English",

series = "2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "164--168",

booktitle = "2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023",

address = "United States",

}

Vargas, MT, Valle, LFR, Vera, DP & Moreno, DG 2023, Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru. in 2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023. 2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023, Institute of Electrical and Electronics Engineers Inc., pp. 164-168, 5th International Conference on Robotics and Computer Vision, ICRCV 2023, Nanjing, China, 15/09/23. https://doi.org/10.1109/ICRCV59470.2023.10329180

Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru. / Vargas, Miguel Torres; Valle, Luis Fernando Rojas; Vera, Diego Porras et al.
2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 164-168 (2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023).

Research output: Chapter in Book/Report › Conference contribution › peer-review

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AU - Vera, Diego Porras

AU - Moreno, Daniel Gamarra

PY - 2023

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AB - Facial recognition systems on learning platforms like Moodle enable fast and efficient evaluation, automating the detection of impersonation in online exams. This project implements a Moodle plugin that performs facial recognition on the student attempting to take a quiz. It consists of two parts for authentication through a webcam: the first part occurs before accessing the quiz, and the second part involves surveillance through a camera during the quiz. The plugin was developed using the PHP and JavaScript programming languages, as well as Face-api. The JavaScript API detects and recognizes faces in the web browser using Tiny Yolo v2 and FaceRecognizerNet. It compares a student's photo or image with the image from their webcam while they are taking the quiz. The Moodle plugin achieved an average error probability of 39.39% for face detection similarity distance.

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AN - SCOPUS:85181540808

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SP - 164

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PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Vargas MT, Valle LFR, Vera DP, Moreno DG. Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru. In 2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 164-168. (2023 5th International Conference on Robotics and Computer Vision, ICRCV 2023). doi: 10.1109/ICRCV59470.2023.10329180

Moodle plugin for real-time face recognition in online exams for Systems Engineering and Computer Science students at Universidad Continental, Huancayo, Peru

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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Cite this