Masked FER-2013: Augmented Dataset for Facial Expression Recognition

Bin Han, Hanseob Kim, Gerard Jounghyun Kim, Jae In Hwang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This poster introduces the Masked FER-2013 dataset that can be used to analyze facial emotions in people wearing masks and train a recognizer. The FER-2013 dataset containing face images annotated with seven emotions was modified by synthesizing mask images into the lower portion of the face. Based on the quantitative evaluation, our dataset can improve the accuracy of CNN, VGG, and ResNet models' emotion recognition in masked images by a maximum of 46%. Additionally, as a use case, we present an application that recognizes the emotions of a masked person, generates emotional face animation, and augments it on a real mask during video conferencing.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages747-748
Number of pages2
ISBN (Electronic)9798350348392
DOIs
Publication statusPublished - 2023
Event2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023 - Shanghai, China
Duration: 2023 Mar 252023 Mar 29

Publication series

NameProceedings - 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023

Conference

Conference2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2023
Country/TerritoryChina
CityShanghai
Period23/3/2523/3/29

Bibliographical note

Funding Information:
This work was supported by the National Research Council of Science & Technology(No. CRC-20-02-KIST).

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Artificial intelligence
  • Computer vision
  • Computing methodologies
  • Human computer interaction (HCI)
  • Human-centered computing
  • Interaction paradigms-Mixed / augmented reality
  • Object recognition

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Media Technology

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