Objective Quality Assessment

For the assessment of video quality, typically subjective tests are carried out. However, these tests are time-consuming and expensive. Œus, numerous e‚orts are being made to predict the video quality through video quality assessment (VQA) metrics. Depending on the availability and the amount of reference information, objective video quality assessment (VQA) algorithms can be categorized into full-reference (FR), reduced-reference (RR), and no-reference (NR) metrics. So far, these metrics have been developed and tested for non-gaming videos, usually considering video on demand (VoD) streaming applications.

Objective quality models enable us to monitor and measure the current quality level of a multimedia service. Although subjective quality assessment is a more reliable and more accurate way to measure the quality of a multimedia service, it is time consuming and expensive to monitor the quality of a provided service subjectively. Therefore, service providers are interested in developing new quality models for their system such as Netflix which recently proposed a new video quality metric called VMAF.

Video quality metrics can be used for monitoring the QoE. If you are intrested in QoE monitoring tools, you can read the following report of “QoS/QoE Monitoring Tools”: Link

You can read more about video and image quality metrics please visit Prof. Bovik webpage.

List of Publications with respect to gaming video quality metrics and models are as follows:
  1. S.Zadtootaghaj, S.Schmidt, N.Barman, S.Möller, M.Martini “ A Classification
    of Video Games based on Game Characteristics linked to Video Coding
    Complexity ,”Annual Workshop on Network and Systems Support for Games
    (Netgames), 2018.
  2. N.Barman, S.Zadtootaghaj, S.Schmidt, M.Martini, S.Möller “ GamingVideoSET:
    A Dataset for Gaming Video Streaming Applications
    ,”Annual Workshop on Network and Systems Support for Games (Netgames), 2018.
  3. N.Barman, S.Zadtootaghaj, S.Schmidt, M.Martini, S.Möller “ An Evaluation
    of Video Quality Assessment Metrics for Gaming Video Streaming,”Packet
    Video Workshop (PV), 2018.
  4. S.Zadtootaghaj, S.Schmidt , S.Möller “ Modeling Gaming QoE: Towards
    the Impact of Frame Rate and Bit Rate on Cloud Gaming,”International
    Conference on Quality of Multimedia Experience (QoMEX), 2018.
  5. N.Barman, S.Zadtootaghaj, M.Martini, S.Möller “ A Comparative Quality
    Assessment Study for Gaming and Non-Gaming Videos,”International Conference
    on Quality of Multimedia Experience (QoMEX), 2018.