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TU Berlin

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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

Schmidt, Steven and Zadtootaghaj, Saman and Schiffner, Falk and Möller, Sebastian and Shafiee Sabet, Saeed and Griwodz, Carsten and Barman, Nabajeet and Martini, Maria G. (2018). Data Assessment for an Opinion Model Predicting Gaming QoE (G.OMG). , 1–16.


Schmidt, Steven and Shafiee Sabet, Saeed and Zadtootaghaj, Saman and Möller, Sebastian and Griwodz, Carsten and Barman, Nabajeet and Martini, Maria G. (2019). Proposal of a Content Classification for Cloud Gaming Services. , 1–10.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian and Barman, Nabajeet and Martini, Maria G.and Shafiee Sabet, Saeed and Griwodz, Carsten (2019). Performance Evaluation of the Opinion Model Predicting Gaming QoE (G.OMG). , 1–9.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian and Barman, Nabajeet and Martini, Maria G.and Shafiee Sabet, Saeed and Griwodz, Carsten (2019). Opinion Model Predicting Gaming QoE (G.OMG). , 1–13.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian and Shafiee Sabet, Saeed (2019). Proposal for an Opinion Model Predicting Gaming QoE for Mobile Online Gaming. , 1–5.


Schmidt, Steven and Zadtootaghaj, Saman and Utke, Markus and Möller, Sebastian and Barman, Nabajeet and Martini, Maria G. and Shafiee Sabet, Saeed and Griwodz, Carsten (2019). First Draft for an Opinion Model Predicting Gaming QoE (G.OMG). , 1–21.


Schmidt, Steven and Naderi, Babak and Sabet, Saeed Shafiee and Zadtootaghaj, Saman and Carsten and Möller, Sebastian (2020). Assessing Interactive Gaming Quality of Experience using a Crowdsourcing Approach. 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX). IEEE, 1–6.


Schmidt, Steven and Shafiee Sabet, Saeed and Naderi, Babak and Zadtootaghaj, Saman and Griwodz, Carsten and Möller, Sebastian (2020). Evaluation of Interactive Test Paradigm for P.CROWDG Recommendation. , 1–7.


Schmidt, Steven and Uhrig, Stefan and Reuschel, Domenic (2020). Investigating the Relationship of Mental Immersion and Physiological Measures during Cloud Gaming. 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX). IEEE, 1–6.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian (2020). Corrigendum for ITU-T Recommendation G.1072: Opinion Model Predicting Gaming QoE. , 1–17.


Schmidt, Steven and Zadtootaghaj, Saman and Shafiee Sabet, Saeed and Möller, Sebastian (2020). Report about Opinion Model for Mobile Online Gaming Applications (G.OMMOG). , 1–9.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian (2017). Update on the Proposal for a Draft New Recommendation on Subjective Evaluation Methods for Gaming Quality (P.GAME). , 1–29.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian (2017). Towards the delay sensitivity of games: There is more than genres. 2017 Ninth International Conference on Quality of Multimedia Experience (QoMEX). IEEE, 1–6.


Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian and Metzger, Florian and Hirth, Matthias and Sužnjević, Mirko (2017). 2nd Update on the Proposal for a Draft New Recommendation on Subjective Evaluation Methods for Gaming Quality (P.GAME). , 1–33.


Sabet, Saeed Shafiee and Griwodz, Carsten and Schmidt, Steven and Zadtootaghaj, Saman and Möller, Sebastian (2018). Towards Applying Game Adaptation to Decrease the Impact of Delay on Quality of Experience. IEEE ISM 2018 – The 20th IEEE International Symposium on Multimedia. IEEE, 1–6.


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