Cited by 171Image and Video Quality AssessmentNetwork Traffic and Congestion ControlMultimedia Communication and Technology

QoE in Video Transmission: A User Experience-Driven Strategy

Zhao, Tiesong, Liu, Qian, Chen, Chang Wen·2017·IEEE Communications Surveys & Tutorials

Abstract

The increasing popularity of video (i.e., audio-visual) applications or services over both wired and wireless links has prompted recent growing interests in the investigations of quality of experience (QoE) in online video transmission. Conventional video quality metrics, such as peak-signal-to-noise-ratio and quality of service, only focus on the reception quality from the systematic perspective. As a result, they cannot represent the true visual experience of an individual user. Instead, the QoE introduces a user experience-driven strategy which puts special emphasis on the contextual and human factors in addition to the transmission system. This advantage has raised the popularity and widespread usage of QoE in video transmission. In this paper, we present an overview of selected issues pertaining to QoE and its recent applications in video transmission, with consideration of the compelling features of QoE (i.e., context and human factors). The selected issues include QoE modeling with influence factors in the end-to-end chain of video transmission, QoE assessment (including subjective test and objective QoE monitoring) and QoE management of video transmission over different types of networks. Through the literature review, we observe that the context and human factors in QoE-aware video transmission have attracted significant attentions since the past two to three years. A vast number of high quality works were published in this area, and will be highlighted in this survey. In addition to a thorough summary of recent progresses, we also present an outlook of future developments on QoE assessment and management in video transmission, especially focusing on the context and human factors that have not been addressed yet and the technical challenges that have not been completely solved so far. We believe that our overview and findings can provide a timely perspective on the related issues and the future research directions in QoE-oriented services over video communications.

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Crossref · 10.1109/comst.2016.2619982

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Authors
Zhao, T., Liu, Q., & Chen, C. W.
Affiliations
  • University at Buffalo, State University of New York (US)
  • Dalian University of Technology (CN)
Venue
IEEE Communications Surveys & Tutorials
Published
2017
Volume
19
Issue
1
Pages
285-302
ISSN
1553-877X (ISSN-L)
OpenAlex
W2537533866
Cited by
171
References
181
Citations by year
2026: 9 · 2025: 13 · 2024: 15 · 2023: 18 · 2022: 14 · 2021: 20 · 2020: 22 · 2019: 24 · 2018: 32 · 2017: 4
FWCI
13.57
Type
journal article
Language
en
Open access
closed
Locations
IEEE Communications Surveys & Tutorials (publishedVersion)
Funders
  • National Natural Science Foundation of China (61671152, 91538203, 61601080)
  • U.S. National Science Foundation (ECCS-1405594)
  • New York State Empire Innovation Program
  • Huawei Gift Funding
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Video Quality Assessment
  • Physical Sciences › Computer Science › Computer Networks and Communications › Network Traffic and Congestion Control
  • Social Sciences › Sociology and Political Science › Multimedia Communication and Technology
Keywords
quality of experience, user experience, QoE modeling, QoE management, human factors, video quality metrics

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