QoE in Video Transmission: A User Experience-Driven Strategy
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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Self-citationQoE management for video conferencing applications
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Mechanisms for QoE optimisation of video traffic: a review paper \n
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A QoE Evaluation Methodology for HD Video Streaming Using Social Networking
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Evaluating the influence of expectations, price and content selection on video quality perception
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Mechanisms for QoE optimisation of Video Traffic: A review paper
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A Novel Strategy to Evaluate QoE for Video Service Delivered over HTTP Adaptive Streaming
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A comparison between SVC and transcoding
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Modeling subjective quality evaluations for mobile video watching in a living lab context
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Regulating QoE for adaptive video streaming using BBF method
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Exploiting bit-depth scaling for quality-scalable energy efficient display processing
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Self-citationQoE analysis for scalable video adaptation
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Video quality ruler: A new experimental methodology for assessing video quality
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The impact of interactivity on the QoE: A preliminary analysis
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QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey
Barakabitze, A. A., Barman, N., Ahmad, A., Zadtootaghaj, S., Sun, L., Martini, M. G., & Atzori, L. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2958784 · Cited by 239 · see citing works
A Survey of Emerging Concepts and Challenges for QoE Management of Multimedia Services
Skorin-Kapov, L., Varela, M., Hoßfeld, T., & Chen, K.-T. (2018) · ACM Transactions on Multimedia Computing, Communications, and Applications · doi:10.1145/3176648 · Cited by 116 · see citing works
Survey on QoE Assessment Approach for Network Service
Yang, M., Wang, S., Calheiros, R. N., & Yang, F. (2018) · IEEE Access · doi:10.1109/access.2018.2867253 · Cited by 54 · see citing works
Pal, D., Vanijja, V., Arpnikanondt, C., Zhang, X., & Papasratorn, B. (2019) · IEEE Access · doi:10.1109/access.2019.2917061 · Cited by 39 · see citing works
- 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
- Semantic Scholar
- 7c331f755de54f5d37d699b6192ca2f2468c8d9b
- 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
- Licence
- 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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