User Generated HDR Gaming Video Streaming Dataset

Introduction

Gaming video streaming applications such as Twitch.tv have gained much attention in recent years and are currently responsible for a significant share of video streaming over the internet. Unlike traditional Video on Demand (VoD) streaming services, gaming videos are streamed live and hence need to be encoded in real-time. Such video encoding cannot exploit the optimized encoding settings such as longer presets and multiple passes. Besides, gaming videos, unlike regular, non-gaming videos consist of artificial scenes and hence may be perceived differently by end users. An openly available dataset allows researchers to gain comparable and more generalizable results, e.g., for video quality assessment, Quality of Experience (QoE) prediction modelling, and selection of optimized encoding settings.

Towards this end, we present GamingHDRVideoSET, a dataset consisting of 18 high-quality gaming videos of 10 seconds duration, 3840x2160 resolution, 10bit, HDR and 30 fps for the research community working on gaming video quality assessment. 384 distorted video sequences obtained by encoding the reference videos using H.264/MPEG-AVC, H.265/MPEG-HEVC, VP9 and AV1 codec standards in 4 different bitrate values (6, 12, 18 and 24 Mbps) and Objective quality assessment results in terms of PSNR and HDR-VQM of the video sequences are also provided.

In addition, six Gaming videos from three games of the same properties as above but of 60 fps are also provided. Kindly note that these videos were not used in the related research publication.

Note: The dataset is designed in accordance with the already publicly available gaming video dataset, GamingVideoSET which can be downloaded by clicking here and KUGVD here

The dataset is available for non-commercial purpose.

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Dataset 

Paper [ArXiv] [IEEE]

Citation

If you use this dataset in your work, kindly cite our paper:

N. Barman and M. G. Martini, "User Generated HDR Gaming Video Streaming: Dataset, Codec Comparison, and Challenges," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 32, no. 3, pp. 1236-1249, March 2022, doi: 10.1109/TCSVT.2021.3077384.