Home > Research > Publications & Outputs > QoE Assessment for Multi-Video Object Based Media

Electronic data

  • ai4me_qomex_2022

    Rights statement: ©2022 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

    Accepted author manuscript, 1.31 MB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

Links

Text available via DOI:

View graph of relations

QoE Assessment for Multi-Video Object Based Media

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date7/09/2022
Host publication2022 14th International Conference on Quality of Multimedia Experience (QoMEX)
PublisherIEEE
Number of pages4
ISBN (electronic)9781665487948
ISBN (print)9781665487955
<mark>Original language</mark>English
Event2022 14th International Conference on Quality of Multimedia Experience (QoMEX) - Lippstadt, Germany
Duration: 5/09/20227/09/2022
https://qomex2022.itec.aau.at/

Conference

Conference2022 14th International Conference on Quality of Multimedia Experience (QoMEX)
Abbreviated titleQoMEX 2022
Country/TerritoryGermany
CityLippstadt
Period5/09/227/09/22
Internet address

Conference

Conference2022 14th International Conference on Quality of Multimedia Experience (QoMEX)
Abbreviated titleQoMEX 2022
Country/TerritoryGermany
CityLippstadt
Period5/09/227/09/22
Internet address

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.

Bibliographic note

©2022 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.