Student authentication by updated facial information with weighting coefficient in e-Learning

Taisuke Kawamata, Takatoshi Ishii, Susumu Fujimori, Takako Akakura

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

E-Learning is effective for reducing time and space limitations for learners. However, one drawback is that user authentication generally employs only login credentials, making cheating easy. We examine variations in facial images in e-Learning with the aim of detecting spoofing. We propose an authentication method that updates registered image using sequential facial images taken by a webcam during e-Learning sessions. This paper examines update timing and procedures, and finds that the updating based on weighted summation of facial feature vectors at students' operation timing maximizes authentication accuracy.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE Region 10 Conference, TENCON 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages551-555
Number of pages5
ISBN (Electronic)9781509025961
DOIs
Publication statusPublished - 8 Feb 2017
Event2016 IEEE Region 10 Conference, TENCON 2016 - Singapore, Singapore
Duration: 22 Nov 201625 Nov 2016

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450

Conference

Conference2016 IEEE Region 10 Conference, TENCON 2016
Country/TerritorySingapore
CitySingapore
Period22/11/1625/11/16

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