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TU Berlin

Inhalt des Dokuments

Steven Schmidt


Research Field

  • Quality of Experience (QoE) for Cloud Gaming Services
  • Engagement in Virtual Reality

Research Topics

  • Identification and quantification of perceptual quality dimensions for gaming QoE
  • Prediction of gaming QoE based on encoding and network parameters
  • Classification of game content
  • Crowdsourcing for gaming evaluation


Steven Schmidt received his M.Sc. degree in Electrical Engineering at the TU Berlin with a major in Communication Systems. Since 2016 he is employed as a research assistant at the Quality and Usability Lab where he is working towards a PhD in the field of Quality of Experience in Mobile Gaming. 


ITU-T SG12 Activities:

  • ITU-T Rec. G.1032 - Influence Factors on Gaming Quality of Experience (2017)
  • ITU-T Rec. P.809 - Subjective Evaluation Methods for Gaming Quality (2018)
  • ITU-T Rec. G.1072 - Opinion Model Predicting Gaming QoE for Cloud Gaming Services (2020)


Quality and Usability Lab
Technische Universität Berlin
Ernst-Reuter-Platz 7
D-10587 Berlin, Germany

Tel:  +49 151 12044969


An Overview of Concepts and Evaluation Methods for Computer Gaming QoE
Zitatschlüssel moeller2013i
Autor Möller, Sebastian and Schmidt, Steven and Beyer, Justus
Buchtitel Fifth Int. Workshop on Quality of Multimedia Experience 2013 (QoMEX 2013)
Seiten 236–241
Jahr 2013
DOI 10.1109/QoMEX.2013.6603243
Ort Klagenfurt am Wörthersee, Austria
Monat 3-5 July
Verlag IEEE
Wie herausgegeben full
Zusammenfassung With the advent of computer games, game providers try to improve their users' experience by ensuring high platform and transmission performance, by developing new interaction techniques and more interesting interfaces, or by launching new game ideas. However, it is still unclear how this affects user-perceived Quality of Experience (QoE). In this paper, we provide an overview of the most-discussed concepts in computer gaming evaluation, taking the perspective of a quality engineer who identifies influence factors, quantifies them in terms of performance metrics, and analyzes their impact on perceived quality features. The concepts are grouped in terms of a taxonomy which can be used for developing empirical test methods as well as instrumental prediction models for computer gaming QoE.
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