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Crowdsourcing based subjective quality assessment of adaptive video streaming
Blekinge Institute of Technology.
Technical University of Denmark.
Telecom SudParis.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. Acreo Swedish ICT. (Realistic3D)ORCID iD: 0000-0001-5060-9402
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2014 (English)In: Vol: Proc. 6th International Workshop on Quality of Multimedia Experience (QoMEX 2014), Singapore: IEEE conference proceedings, 2014, p. 53-54Conference paper, Published paper (Refereed)
Abstract [en]

In order to cater for user’s quality of experience (QoE) requirements, HTTP adaptive streaming (HAS) based solutions of video services have become popular recently. User QoE feedback can be instrumental in improving the capabilities of such services. Perceptual quality experiments that involve humans are considered to be the most valid method of the assessment of QoE. Besides lab-based subjective experiments, crowdsourcing based subjective assessment of video quality is gaining popularity as an alternative method. This paper presents insights into a study that investigates perceptual preferences of various adaptive video streaming scenarios through crowdsourcing based subjective quality assessment.

Place, publisher, year, edition, pages
Singapore: IEEE conference proceedings, 2014. p. 53-54
Keywords [en]
Adaptive streaming, Subjective, Video quality assessment, Crowdsourcing, Buffering
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:miun:diva-24537DOI: 10.1109/QoMEX.2014.6982289OAI: oai:DiVA.org:miun-24537DiVA, id: diva2:794433
Conference
6th International Workshop on Quality of Multimedia Experience (QoMEX 2014)
Available from: 2015-03-11 Created: 2015-03-11 Last updated: 2025-09-25Bibliographically approved

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Brunnström, KjellWang, Kun

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf