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

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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.

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Vijayakumar, S., Corcoran, P., Flynn, R., & Murray, N. (2022). Research Proposal: AI-derived Quality of Experience Prediction based on Physiological Signals for Immersive Multimedia Experiences. In MMSys 2022 - Proceedings of the 13th ACM Multimedia Systems Conference (pp. 403–407). Association for Computing Machinery, Inc. https://doi.org/10.1145/3524273.3533935

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