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Steven Schmidt
- © Q&U
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
| Citation key | barman2018b |
|---|---|
| Author | Barman, Nabajeet and Schmidt, Steven and Zadtootaghaj, Saman and Martini, Maria G. and Möller, Sebastian |
| Title of Book | 16th Annual Workshop on Network and Systems Support for Games (NetGames) |
| Pages | 1–6 |
| Year | 2018 |
| ISSN | 2156-8146 |
| DOI | 10.1109/NetGames.2018.8463362 |
| Address | Piscataway, NJ |
| Month | jun |
| Note | electronic |
| Publisher | IEEE |
| How Published | full |
| Abstract | This paper presents GamingVideoSET1, a dataset consisting of twenty-four uncompressed raw gaming videos of 30 seconds duration, 1080p resolution, and 30 fps for the research community working on gaming video quality assessment. Furthermore, the data set includes subjective quality assessment results for 90 video sequences obtained by encoding six different gaming videos using the H.264/MPEG-AVC codec standard in 15 different resolution-bitrate pairs (three resolution, five bitrates each). In addition to the reference videos, the dataset offers a total of 576 distorted videos in MP4 format, obtained by encoding the videos in 24 different resolution-bitrate pairs, and their objective quality assessment results (average and per-frame) using three video quality assessment metrics.1The database is available at https://kingston.box.com/v/GamingVideoSET |