Recognizing student facial expressions: A web application

Andreas Savva, Vasso Stylianou, Kyriacos Kyriacou, Florent Domenach

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

Abstract

The project described in this paper investigates the idea of performing emotion analysis of a student population participating in active face-To-face classroom instruction. Machine learning algorithms are employed on live recordings collected by webcams that are installed in classrooms. The visualization application required to be remotely accessible by the lecturer so the application was engineered as a web application. The output, being a timeline of student emotions monitored throughout and in parallel with the lecture, serves to enable the lecturer and other interested parties to improve the delivery of education.

Original languageEnglish
Title of host publicationProceedings of 2018 IEEE Global Engineering Education Conference
Subtitle of host publicationEmerging Trends and Challenges of Engineering Education, EDUCON 2018
PublisherIEEE Computer Society
Pages1459-1462
Number of pages4
Volume2018-April
ISBN (Electronic)9781538629574
DOIs
Publication statusPublished - 23 May 2018
Event2018 IEEE Global Engineering Education Conference - Emerging Trends and Challenges of Engineering Education, EDUCON 2018 - Santa Cruz de Tenerife, Canary Islands, Spain
Duration: 17 Apr 201820 Apr 2018

Conference

Conference2018 IEEE Global Engineering Education Conference - Emerging Trends and Challenges of Engineering Education, EDUCON 2018
Country/TerritorySpain
CitySanta Cruz de Tenerife, Canary Islands
Period17/04/1820/04/18

Keywords

  • Emotion Analysis
  • Facial Expressions
  • Machine Learning

Fingerprint

Dive into the research topics of 'Recognizing student facial expressions: A web application'. Together they form a unique fingerprint.

Cite this