Facial Emotion recognition analysis using deep learning through RGB-D imagery of VR participants through partially occluded facial types

Research output: Contribution to conferencePosterpeer-review

Abstract

This research poster outlines the initial development of a facial emotion recognition (FER) evaluation system based on RGB-D imagery captured via a mobile based device. The study outlined features control group of non-occluded facial types and a set of participants wearing a head mounted display (HMD) in order to demonstrate an occluded facial type. We explore an architecture to develop a FER system that is suitable for occluded facial analysis. This paper details the methodology, experimental design and future work to be carried out to deliver such a system.

Original languageEnglish
Pages862-863
Number of pages2
DOIs
Publication statusPublished - 2022
Event2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022 - Virtual, Online, New Zealand
Duration: 12 Mar 202216 Mar 2022

Conference

Conference2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022
Country/TerritoryNew Zealand
CityVirtual, Online
Period12/03/202216/03/2022

Keywords

  • Accessibility
  • Accessibility Technologies
  • Collaborative and Social Computing
  • Human computer interaction
  • Human Computer Interaction (HCI)
  • Human-centered computing
  • Interaction Design
  • Interaction paradigms
  • Virtual reality
  • Visualization

Fingerprint

Dive into the research topics of 'Facial Emotion recognition analysis using deep learning through RGB-D imagery of VR participants through partially occluded facial types'. Together they form a unique fingerprint.

Cite this