Facial recognition for user validation during a questionnaire in Moodle

• Daniel Gonçalves da Silva UFABC
• Francisco de Assis Zampirolli UFABC

DOI: https://doi.org/10.5753/cbie.wcbie.2020.124

Abstract

Online assessments are increasingly present. This is even more evident with the great demand resulting from the 2020 pandemic. However, verifying the authenticity of the appraised is a task that still needs new solutions. In this sense, this work presents the Face Verification Quiz plugin for Moodle, a Learning Management System widely used at different levels of education. Pre-trained Deep Convolutional Neural Networks were used to quickly detect the contour of the face using pixels from the eyes, nose and mouth. Another network was used for facial recognition, with 128 characteristics. This facial verification service is executed in the client's browser when accessing a questionnaire in Moodle.

Keywords: Facial Recognition, User Validation, Moodle, Online Assessment

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