Research Proposal: AI-derived Quality of Experience Prediction based on Physiological Signals for Immersive Multimedia Experiences

Sowmya Vijayakumar, Peter Corcoran, Ronan Flynn, Niall Murray

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

3 Citations (Scopus)

Abstract

This paper contains the research proposal of Sowmya Vijayakumar that was presented at the MMSys 2022 doctorial symposium. Multimedia applications can now be found across many application domains including but not limited to entertainment, communication, health, business, and education. It is becoming more and more important to understand the factors that influence user perceptual quality, and hence monitoring user quality of experience (QoE) for improving multimedia interaction and services is essential. In this PhD work, we propose advanced machine learning techniques to predict QoE from physiological signals for immersive multimedia experiences. The aim of this doctoral study is to investigate the utility of physiological responses for QoE assessment for different multimedia technologies. Here, the research questions and solutions proposed to address this challenge are presented. A multimodal QoE prediction model is being developed that integrates several physiological measurements to improve QoE prediction performance.

Original languageEnglish
Title of host publicationMMSys 2022 - Proceedings of the 13th ACM Multimedia Systems Conference
PublisherAssociation for Computing Machinery, Inc
Pages403-407
Number of pages5
ISBN (Electronic)9781450392839
DOIs
Publication statusPublished - 14 Jun 2022
Event13th ACM Multimedia Systems Conference, MMSys 2022 - Athlone, Ireland
Duration: 14 Jun 202217 Jun 2022

Publication series

NameMMSys 2022 - Proceedings of the 13th ACM Multimedia Systems Conference

Conference

Conference13th ACM Multimedia Systems Conference, MMSys 2022
Country/TerritoryIreland
CityAthlone
Period14/06/2217/06/22

Keywords

  • Deep learning
  • Immersive multimedia systems
  • Machine learning
  • Physiological signals
  • Quality of experience

Fingerprint

Dive into the research topics of 'Research Proposal: AI-derived Quality of Experience Prediction based on Physiological Signals for Immersive Multimedia Experiences'. Together they form a unique fingerprint.

Cite this