Embracing uncertainty: A probabilistic view of HTTP video quality

Martín Varela, Toni Mäki

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

When dealing with Quality of Experience (QoE) and in particular perceptual quality assessment and modeling, averaging is a common occurrence. For instance, the most commonly used measure of QoE is the aptly-called Mean Opinion Score (MOS), which is intended to represent an idealized average subject's rating of the quality. Another form of averaging occurs when choosing and preparing the samples used for the assessment, which are supposed to be representative of an average viewing situation. This leads to nice, smooth scalar representations of quality, but at the same time, it leads to a loss of information. In this paper we present a first step towards working with all the information available in an explicit way, rather than averaging it away. We do so in the context of constructing layered quality models for HTTP video streaming (using Dynamic Adaptive HTTP Streaming - DASH, excluding its adaptation feature at this stage), mapping network-level QoS measurements to probability distributions of different MOS values for a given set of conditions.

Original languageEnglish
Title of host publicationProceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network and Service Management
EditorsProsper Chemouil, Paulo Simoes, Edmundo Madeira, Stefano Secci, Edmundo Monteiro, Luciano Paschoal Gaspary, Carlos Raniery P. dos Santos, Marinos Charalambides
PublisherIEEE
Pages1023-1026
Number of pages4
ISBN (Electronic)9783901882890
DOIs
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventIFIP/IEEE International Symposium on Integrated Network and Service Management - Lisbon, Portugal
Duration: 8 May 201712 May 2017
Conference number: 15

Conference

ConferenceIFIP/IEEE International Symposium on Integrated Network and Service Management
Abbreviated titleIM
CountryPortugal
CityLisbon
Period08/05/201712/05/2017

Keywords

  • DASH
  • HTTP Video
  • QoE
  • QoS

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