À propos de cet article

Citez

M. Johansson, “Mobile cloud gaming: Network slicing early commercial use cases series,” Ericsson, 2022. [Online]. Available: https://www.ericsson.com/en/blog/2022/6/mobile-cloud-gaming-an-early-use-case-for-network-slicingSearch in Google Scholar

RootMetrics, “Mobile cloud gaming: the real-world cloud gaming experience in Los Angeles,” 2020. [Online]. Available: https://rootmetrics.com/en-US/content/us-LA-gaming-report-2020Search in Google Scholar

Huawei Cloud, “Cloud Gaming Experience Model (Cloud gMOS),” 2019. [Online]. Available: https://www-file.huawei.com/-/media/corporate/pdf/x-lab/2019/cloud_gmos_white_paper_en.pdf?la=enSearch in Google Scholar

A. Wahab, N. Ahmad, M. G. Martini, J. Schormans, “Subjective Quality Assessment for Cloud Gaming,” Multidisciplinary Scientific Journal, vol. 4, no. 3, pp. 404–419, 2021.Search in Google Scholar

J. Baraković Husić, S. Baraković, “Multidimensional modelling of quality of experience for video streaming,” Computers in Human Behaviour, vol. 129, 10715, 2022.Search in Google Scholar

M. I. Jordan, T. M. Mitchell, “Machine learning: Trends, perspectives, and prospects,” Science, vol. 349, pp. 255-60, 2015.Search in Google Scholar

S. Ray, “A Quick Review of Machine Learning Algorithms,” in Proc. 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (Com-IT-Con), India, 2019.Search in Google Scholar

A. Leontaris, A. R. Reibman, “Comparison of blocking and blurring metrics for video compression,” in Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’05), Philadelphia, PA, USA, 2005.Search in Google Scholar

M. Shahid, A. Rossholm, B. Lövström, H.-J. Zepernick, “No-reference image and video quality assessment: a classification and review of recent approaches,” EURASIP Journal on Image and Video Processing, 2014.Search in Google Scholar

H. Choi, C. Lee, “No-reference image quality metric based on image classification,” EURASIP Journal on Advances in Signal Processing, 2011.Search in Google Scholar

Z. Akhtar, T. H. Falk, “Audio-Visual Multimedia Quality Assessment: A Comprehensive Survey,” IEEE Access, vol. 5, pp. 21090 – 21117, 2017.Search in Google Scholar

X. Yu, Z. Ying, N. Birkbeck, Y. Wang, B. Adsumilli, A. C. Bovik, “Subjective and objective analysis of streamed gaming videos,” 2022, arXiv:2203.12824.Search in Google Scholar

N. Barman, S. Schmidt, S. Zadtootaghaj, M. G. Martini, S. Möller, “An evaluation of video quality assessment metrics for passive gaming video streaming,” in Proc. 23rd Packet Video Workshop (PV), The Netherlands, 2018.Search in Google Scholar

N. Barman, S. Zadtootaghaj, M. G. Martini, S. Möller, S. Lee, “A comparative quality assessment study for gaming and non-gaming videos,” in Proc. 10th International Conference Quality Multimedia Experience (QoMEX), Italy, 2018.Search in Google Scholar

N. Barman, M. G. Martini, “H.264/MPEG-AVC, H.265/MPEG-HEVC and VP9 codec comparison for live gaming video streaming,” in Proc. 9th International Conference Quality Multimedia Experience (QoMEX), Germany, 2017.Search in Google Scholar

N. Barman, S. Zadtootaghaj, S. Schmidt, M. G. Martini, S. Möller, “GamingVideoSET: A dataset for gaming video streaming applications,” in Proc. 16th Annual Workshop Network and System Support Games (NetGames), The Netherlands, 2018.Search in Google Scholar

N. Barman, E. Jammeh, S. A. Ghorashi, M. Martini, “No-reference video quality estimation based on machine learning for passive gaming video streaming applications,” IEEE Access, vol. 7, pp. 74511-74527, 2019.Search in Google Scholar

S. Zadtootaghaj, N. Barman, S. Schmidt, M. Martini, S. Möller, “NR-GVQM: A No Reference Gaming Video Quality Metric,” in Proc. International Symposium on Multimedia (ISM), Taiwan, 2018.Search in Google Scholar

S. Zadtootaghaj, N. Barman, R. R. Ramachandra Rao, S. Göring, M. Martini, A. Raake, S. Möller, “DEMI: Deep video quality estimation model using perceptual video quality dimensions,” in Proc. 22nd International Workshop on Multimedia Signal Processing (MMSP), Finland, 2020.Search in Google Scholar

M. Utke, S. Zadtootaghaj, S. Schmidt, S. Bosse, S. Möller, “NDNetGaming - development of a noreference deep CNN for gaming video quality prediction,” Multimedia Tools and Applications, vol. 81, pp. 3181–3203, 2020.Search in Google Scholar

S. Van Damme, M. Torres Vega, J. Heyse, F. De Backere F., De Turck, “A low-complexity psychometric curve-fitting approach for the objective quality assessment of streamed game videos,” Signal Processing: Image Communication, vol. 88, 115954, 2020.Search in Google Scholar

S. Göring, R. R. Ramachandra Rao, A. Raake, “nofu -a lightweight no-reference pixel-based video quality model for gaming content,” in Proc. 11th International Conference on Quality of Multimedia Experience (QoMEX), Germany, 2019.Search in Google Scholar

Steam. (2023). [Online]. Available: https://store.steampowered.com/about/Search in Google Scholar

Steam Link. (2023). [Online]. Available: https://store.steampowered.com/app/353380/Steam_Link/Search in Google Scholar

Wireshark. (2023). [Online]. Available: https://www.wireshark.org/Search in Google Scholar

Aiseesoft Screen Recorder. (2023). [Online]. Available: https://www.aiseesoft.com/screen-recorder/Search in Google Scholar

MSU Video Group: Video filtering and compression. (2023). [Online]. Available: https://www.compression.ru/video/Search in Google Scholar

MATLAB: Math. Graphics. Programming. (2023). [Online]. Available: https://www.mathworks.com/products/matlab.htmlSearch in Google Scholar

WEKA: The Data Platform for the cloud & AI Era. (2023). [Online]. Available: https://www.weka.io/Search in Google Scholar

M. Gong, “A Novel Performance Measure for Machine Learning Classification,” International Journal of Managing Information Technology (IJMIT), vol. 13, no. 1, 2021.Search in Google Scholar

G. Kougioumtzidis, V. Poulkov, Z. D. Zaharis, P. I. Lazaridis, “A Survey on Multimedia Services QoE Assessment and Machine Learning-Based Prediction,” IEEE Access, vol. 10, pp. 19507-19538, 2022.Search in Google Scholar

D. Vučić, L. Skorin-Kapov, “QoE assessment of mobile multiparty audiovisual telemeetings,” IEEE Access, vol. 8, pp. 107669-107684, 2020.Search in Google Scholar

C. Baena, O. S. Peñaherrera-Pulla, R. Barco, S. Fortes, “Measuring and estimating Key Quality Indicators in Cloud Gaming services,” Computer Networks, 109808, 2023.Search in Google Scholar

O. Izima, R. de Fréin, A. Malik, “A Survey of Machine Learning Techniques for Video Quality Prediction from Quality of Delivery Metrics,” Electronics, vol. 10, no. 22, 2851, 2021.Search in Google Scholar

P. Casas, S. Wassermann, “Improving QoE prediction in mobile video through machine learning,” in Proc. of 8th Int. Conf. Netw. Future (NOF), London, UK, 2017.Search in Google Scholar

S. S. Sabet, M. R. Hashemi, S. Shirmohammadi, M. Ghanbari, “A Novel Objective Quality Assessment Method for Perceptually-Coded Cloud Gaming Video,” in Proc. IEEE Conference on Multimedia Information Processing and Retrieval (MIPR), Miami, FL, USA, 2018.Search in Google Scholar