QoE Assessment for Multi-Video Object Based Media

Lyko, T., Elkhatib, Y. , Sparks, M., Race, N. and Ramdhany, R. (2022) QoE Assessment for Multi-Video Object Based Media. In: 2022 14th International Conference on Quality of Multimedia Experience (QoMEX), Lippstadt, Germany, 05-07 Sep 2022, ISBN 9781665487948 (doi: 10.1109/QoMEX55416.2022.9900905)

Abstract

Recent multimedia experiences using techniques such as DASH allow the streaming delivery to be adapted to suit network context. Object Based Media (OBM) provides even more flexibility as distinct media objects are streamed and combined based on user preferences, allowing the experience to be personalised for the user. As adaptation can lead to degradation, modelling and measuring Quality of Experience (QoE) are crucial to ensure a perceptibly-optimal user experience. QoE models proposed for DASH include quality-related factors from single video-object streams and hence, are unsuitable for multi-video OBM experiences. In this paper, we propose an objective method to quantify QoE for video-based OBM experiences. Our model provides different strategies to aggregate individual object QoE contributions for different OBM experience genres. We apply our model to a case study and contrast it with the QoE levels obtained using a standard QoE model for DASH.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Elkhatib, Dr Yehia
• Authors: Lyko, T., Elkhatib, Y., Sparks, M., Race, N., and Ramdhany, R.
• College/School: College of Science and Engineering > School of Computing Science
• ISSN: 2472-7814
• ISBN: 9781665487948
• Published Online: 04 October 2022
• Copyright Holders: Copyright © 2022 IEEE
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

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