• DocumentCode
    3534575
  • Title

    QoE-based evaluation model on video streaming service quality

  • Author

    Yun Shen ; Yitong Liu ; Nan Qiao ; Lin Sang ; Dacheng Yang

  • Author_Institution
    Wireless Theor. & Technol. (WT&T) Lab., Beijing Univ. of Posts & Telecommun., Beijing, China
  • fYear
    2012
  • fDate
    3-7 Dec. 2012
  • Firstpage
    1314
  • Lastpage
    1318
  • Abstract
    The growing demand on video streaming services is the main motive power for video quality assessment. Due to the rapid development of video streaming services, customers are more enjoying higher quality videos, and their perceptions on video service will directly influence the service provider´s performance, which makes it significant to study end-users´ subjective perception, named as Quality of Experience (QoE), on video streaming for both service providers and end-users. In this paper, a QoE evaluation model is proposed to predict the end-users´ perception on video streaming service considering different video content types. This QoE model, named as Video-Mean Opinion Score (VMOS) model, directly focuses on end-users´ feeling. Thus, the Key Performance Indicators (KPIs), which can be straightly felt by end-users, are mapped to QoE score without considering the network parameters. The excellent performance of VMOS model for QoE evaluation on video quality has been verified via plenty subjective Mean Opinion Score (MOS) test, which includes 180 video samples with 1280 valid votes. The Pearson Correlation Coefficient between VMOS score and MOS is as high as 0.925, which indicates that this model can evaluate users´ perception on video quality with almost the same accuracy as subjective test.
  • Keywords
    correlation methods; quality of experience; statistical analysis; video streaming; KPI; MOS test; Pearson correlation coefficient; QoE score; QoE-based evaluation model; VMOS model; VMOS score; end-user perception; end-user subjective perception; key performance indicator; network parameter; quality of experience; service provider performance; video content type; video quality assessment; video service perception; video streaming service quality; video-mean opinion score; Adaptation models; Bit rate; Correlation coefficient; PSNR; Quality assessment; Streaming media; Video recording; KPIs; MOS; QoE; VMOS model; video quality;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Globecom Workshops (GC Wkshps), 2012 IEEE
  • Conference_Location
    Anaheim, CA
  • Print_ISBN
    978-1-4673-4942-0
  • Electronic_ISBN
    978-1-4673-4940-6
  • Type

    conf

  • DOI
    10.1109/GLOCOMW.2012.6477772
  • Filename
    6477772