GamingVideoSET: a dataset for gaming video streaming applications

Steven Schmidt; Maria G. Martini; Sebastian Möller; Nabajeet Barman; Saman Zadtootaghaj

doi:10.1109/NetGames.2018.8463362

GamingVideoSET: a dataset for gaming video streaming applications

Steven Schmidt, Maria G. Martini, Sebastian Möller, Nabajeet Barman, Saman Zadtootaghaj

Research output: Contribution to conference › Paper › peer-review

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.

Original language	English
DOIs	https://doi.org/10.1109/NetGames.2018.8463362
Publication status	Published - 2018
Event	2018 16th Annual Workshop on Network and Systems Support for Games (NetGames) - Amsterdam, Netherlands Duration: 12 Jun 2018 → 15 Jun 2018

Workshop

Workshop	2018 16th Annual Workshop on Network and Systems Support for Games (NetGames)
Period	12/06/18 → 15/06/18

Bibliographical note

Note: This work was supported by the European Union‘s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie [grant number 643072] and German Research Foundation (DFG) within project MO 1038/21-1. Published in Proceedings of the 2018 16th Annual Workshop on Network and Systems Support for Games (NetGames). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. ISSN (online) 2156-8146 ISBN (electronic) 9781538660980.

Keywords

Computer science and informatics

Access to Document

10.1109/NetGames.2018.8463362

http://dx.doi.org/10.1109/NetGames.2018.8463362

1 Conference contribution

GamingVideoSET: a dataset for gaming video streaming applications
Schmidt, S., Martini, M. G., Möller, S., Barman, N. & Zadtootaghaj, S., 2018, This work was supported by the European Union‘s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie [grant number 643072] and German Research Foundation (DFG) within project MO 1038/21-1. Published in Proceedings of the 2018 16th Annual Workshop on Network and Systems Support for Games (NetGames). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. ISSN (online) 2156-8146 ISBN (electronic) 9781538660980.. Piscataway, U.S.: Institute of Electrical and Electronics Engineers, Inc.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Cite this

@conference{da809e3ef37e4e4680589f8a3eadf7bf,

title = "GamingVideoSET: a dataset for gaming video streaming applications",

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.",

keywords = "Computer science and informatics",

author = "Steven Schmidt and Martini, \{Maria G.\} and Sebastian M{\"o}ller and Nabajeet Barman and Saman Zadtootaghaj",

note = "Note: This work was supported by the European Union{\textquoteleft}s Horizon 2020 research and innovation programme under Marie Sk{\l}odowska-Curie [grant number 643072] and German Research Foundation (DFG) within project MO 1038/21-1. Published in Proceedings of the 2018 16th Annual Workshop on Network and Systems Support for Games (NetGames). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. ISSN (online) 2156-8146 ISBN (electronic) 9781538660980.; 2018 16th Annual Workshop on Network and Systems Support for Games (NetGames) ; Conference date: 12-06-2018 Through 15-06-2018",

year = "2018",

doi = "10.1109/NetGames.2018.8463362",

language = "English",

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AU - Schmidt, Steven

AU - Martini, Maria G.

AU - Möller, Sebastian

AU - Barman, Nabajeet

AU - Zadtootaghaj, Saman

N1 - Note: This work was supported by the European Union‘s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie [grant number 643072] and German Research Foundation (DFG) within project MO 1038/21-1. Published in Proceedings of the 2018 16th Annual Workshop on Network and Systems Support for Games (NetGames). Piscataway, U.S. : Institute of Electrical and Electronics Engineers, Inc. ISSN (online) 2156-8146 ISBN (electronic) 9781538660980.

PY - 2018

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N2 - 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.

AB - 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.

KW - Computer science and informatics

U2 - 10.1109/NetGames.2018.8463362

DO - 10.1109/NetGames.2018.8463362

M3 - Paper

Y2 - 12 June 2018 through 15 June 2018

ER -

GamingVideoSET: a dataset for gaming video streaming applications

Abstract

Workshop

Bibliographical note

Keywords

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Research output

GamingVideoSET: a dataset for gaming video streaming applications

Cite this