An evaluation of video quality assessment metrics for passive gaming video streaming

Barman, Nabajeet, Schmidt, Steven, Zadtootaghaj, Saman, Martini, Maria G. and Möller, Sebastian (2018) An evaluation of video quality assessment metrics for passive gaming video streaming. In: 23rd Packet Video Workshop 2018; 12-15 Jun 2018, Amsterdam, Netherlands.

Full text not available from this archive.

Abstract

Video quality assessment is imperative to estimate the user experience to provide a reasonable Quality of Experience in video streaming applications to the end-user. Recent years have seen a tremendous advancement in the field of video quality assessment (VQA) metrics, with the development of models that can predict the quality of the videos streamed over the Internet. However, no work so far has attempted to study the performance of such quality assessment metrics on gaming videos which are artificial and synthetic and have different streaming requirements than traditionally streamed videos. Towards this end, we present in this paper an objective and subjective quality assessment study of gaming videos considering passive streaming applications. For subjective quality assessment, we consider six different gaming video sequences and 15 resolution-bitrate pairs. Objective quality assessment considering eight widely used VQA metrics is performed on a dataset of 24 reference videos and 576 compressed sequences obtained by encoding them at 24 different resolution-bitrate pairs. We present an evaluation of the performance behavior of the VQA metrics. Our results indicate that VMAF predicts subjective video quality ratings the best, while NIQE turns out to be a very promising alternative as a no-reference metric.

Item Type: Conference or Workshop Item (Paper)
Event Title: 23rd Packet Video Workshop 2018
Organising Body: Association for Computing Machinery Special Interest Group on Multimedia
Additional Information: This paper was published in PV '18 Proceedings of the 23rd Packet Video Workshop (2018), pages 7-12. ISBN: 9781450357739
Research Area: Computer science and informatics
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing
Faculty of Science, Engineering and Computing > School of Computer Science and Mathematics
Related URLs:
Depositing User: Nabajeet Barman
Date Deposited: 03 Jul 2018 17:38
Last Modified: 29 Jan 2019 14:20
URI: http://eprints.kingston.ac.uk/id/eprint/40976

Actions (Repository Editors)

Item Control Page Item Control Page