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Quality and Usability LabAssessment and Prediction of the QoE of Mobile Gaming

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Subjective assessment and instrumental prediction of mobile online gaming on the basis of perceptual dimensions

Motivation

The assessment of the perceived quality of the user (Quality of Experience) of pure audio and video material differs in many ways from the quality of computer games. The later possess a variety of factors due to their interactive nature. Not only factors of complex and innovative game systems have an impact on the QoE, but also the players themselves. A quality judgment, that results by comparing the expected and perceived composition of an entity, depends highly on the preferences, expectations and abilities of the player.

In this still young area of research standard methods for determining the QoE are not directly applicable. This is apparent since in a task oriented human-computer interaction the goal should be achieved with minimal effort. However in a game  the player exerts an effort in order to influence the outcome and thereby feels emotionally attached. Thus new concepts such as immersion and flow, a state of happiness while being in an equilibrium between competence and challenge, appear.

An analysis of the gaming market shows, that the proportion of mobile games has risen sharply in recent years. Mobile games are special in a sense that mobile devices such as smartphones or tablets were originally not designed for games and are therefore not optimally adapted to them. This also applies to the new concept of cloud gaming, where the entire game is executed on a server and only the video and audio material is transferred to the end user.

 

Aim of the project

The aim of this research project is to develop methods to assess the QoE of mobile games. In addition, based on a database containing subjective quality judgments, a model similar to the well known E-model should be constructed to predict the QoE. The following concrete steps are planned for this purpose:

  • Set up and modification of a testbed for conducting experiments including a cloud gaming system for mobile games
  • Development of a classification of games to choose representative games and identify system and user factors
  • Building a questionnaire covering a large space of relevant quality dimensions
  • Identification of quality-relevant perceptual dimensions and analysis of their impact on the overall quality
  • Analyzing the performance of current objective metrics which were proposed for different contents and services in mobile gaming
  • Building a QoE model based on game, system and network characteristics as well as user and context factors
Time Frame: 
01/2016 - 06/2019
T-labs Team Members:
Steven Schmidt
Funding by:
Deutsche Forschungsgemeinschaft (DFG)
Project Number:
MO 1038/21-1

List of Publications

Influence of Network Delay in Virtual Reality Multiplayer Exergames: Who is actually delayed?
Citation key kojic2019b
Author Kojic, Tanja and Schmidt, Steven and Möller, Sebastian and Voigt-Antons, Jan-Niklas
Title of Book 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX)
Pages 1–3
Year 2019
ISSN 2372-7179
DOI 10.1109/QoMEX.2019.8743342
Location Berlin, Germany
Address Piscataway, NJ, USA
Month jun
Note Online
Publisher IEEE
Series QoMEX
How Published Fullpaper
Abstract One of the fields where Virtual Reality (VR) is finding a potentially growing market is in the combination of exercising and gaming - also called exergaming. When it comes to competition in gaming, is important to investigate how different levels of delay influence overall quality of experience (QoE) in VR multiplayer exergames. Therefore, we conducted a subjective experiment using a VR multiplayer exergame. The experimental setup consisted of a VR application coupled with a rowing ergometer, allowing races between the user and an artificially created opponent that is following the player with a similar speed and keeping the race tight. To investigate the influence of the delay, on both user's and opponent's side three levels of network delay were introduced (30ms, 100ms, and 500ms) and mixed throughout different conditions. After each session, participants rated perceived flow, sense of presence, and the degree to which they have noticed the delay in their or the opponent's system. Interestingly, results show different perception of delay and QoE depending on user's own delay. Participants perceived the opponent's player as being delayed even if only the player itself had network delay along with significantly lower rating of QoE only when their delay was high.
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