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
Biography
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.
Projects
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)
Address
Quality and Usability Lab
Technische Universität Berlin
Ernst-Reuter-Platz 7
D-10587 Berlin, Germany
Tel: +49 151 12044969
Publications
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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