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Quality of Experience Modeling for Cloud Gaming Services
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Quality of Experience Modeling for Cloud Gaming Services/ by Saman Zadtootaghaj.
Author:
Zadtootaghaj, Saman.
Description:
XVII, 170 p. 55 illus., 49 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Communications Engineering, Networks. -
Online resource:
https://doi.org/10.1007/978-3-030-98249-2
ISBN:
9783030982492
Quality of Experience Modeling for Cloud Gaming Services
Zadtootaghaj, Saman.
Quality of Experience Modeling for Cloud Gaming Services
[electronic resource] /by Saman Zadtootaghaj. - 1st ed. 2022. - XVII, 170 p. 55 illus., 49 illus. in color.online resource. - T-Labs Series in Telecommunication Services,2192-2829. - T-Labs Series in Telecommunication Services,.
Introduction -- Gaming Quality of Experience -- Process for Model Development -- Video Coding Impairment Models -- Integration of Impairment Factors to Gaming QoE -- Performance Evaluation 95 -- Conclusion.
This book presents the development of a gaming quality model to predict the gaming Quality of Experience (QoE) of players that could be used for planning the network service or quality monitoring of cloud gaming services. The author presents a model that is developed following a modular structure approach that keeps the different types of impairments separately. The book shows how such a modular structure allows developing a sustainable model as each component can be updated by advances in that specific research area or technology. The presented gaming quality model takes into account two modules of video quality and input quality. The latter considers the interactivity aspects of gaming. The video quality module offers a series of models that differ depending on the level of access to the video stream information, allowing high flexibility for service providers regarding the positions of measuring points within their system. In summary, the present book focuses on (1) creation of multiple image/video and cloud gaming quality datasets, (2) development of a gaming video classification, and (3) development of a series of gaming QoE models to predict the gaming QoE depending on the level of access to the video stream information. Introduces a gaming Quality of Experience (QoE) model that can be used to predict the quality of cloud gaming services; Describes multiple video quality models, signal-based, bitstream-based and planning-based models for gaming content; Presents guidelines for conducting the subjective test for assessment of gaming quality for cloud/online gaming.
ISBN: 9783030982492
Standard No.: 10.1007/978-3-030-98249-2doiSubjects--Topical Terms:
669809
Communications Engineering, Networks.
LC Class. No.: TK5101-5105.9
Dewey Class. No.: 621.382
Quality of Experience Modeling for Cloud Gaming Services
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Introduction -- Gaming Quality of Experience -- Process for Model Development -- Video Coding Impairment Models -- Integration of Impairment Factors to Gaming QoE -- Performance Evaluation 95 -- Conclusion.
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This book presents the development of a gaming quality model to predict the gaming Quality of Experience (QoE) of players that could be used for planning the network service or quality monitoring of cloud gaming services. The author presents a model that is developed following a modular structure approach that keeps the different types of impairments separately. The book shows how such a modular structure allows developing a sustainable model as each component can be updated by advances in that specific research area or technology. The presented gaming quality model takes into account two modules of video quality and input quality. The latter considers the interactivity aspects of gaming. The video quality module offers a series of models that differ depending on the level of access to the video stream information, allowing high flexibility for service providers regarding the positions of measuring points within their system. In summary, the present book focuses on (1) creation of multiple image/video and cloud gaming quality datasets, (2) development of a gaming video classification, and (3) development of a series of gaming QoE models to predict the gaming QoE depending on the level of access to the video stream information. Introduces a gaming Quality of Experience (QoE) model that can be used to predict the quality of cloud gaming services; Describes multiple video quality models, signal-based, bitstream-based and planning-based models for gaming content; Presents guidelines for conducting the subjective test for assessment of gaming quality for cloud/online gaming.
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