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  • Format: PDF

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…mehr

Produktbeschreibung
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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Autorenporträt
Saman Zadtootaghaj is a senior research engineer at Dolby laboratories. His main interest is the subjective and objective quality assessment of Computer-Generated content. He worked as a researcher at Telekom Innovation Laboratories of Deutsche Telekom AG from 2016 to 2018 as part of the European project called QoE-Net. He completed his Ph.D. at the Quality Usability lab group of TU Berlin under the supervision of Prof. Dr.-Ing. Sebastian Moller. He is currently the chair of the Computer-Generated Imagery group at Video Quality Expert Group and an active member of ITU-T Study Group 12, leading the P.BBQCG work item. Saman has over 40 publications in multiple conferences and journals, including best paper awards of NetGames workshop 2018. He strongly contributed to the ITU-T SG 12, including over 20 contributions within the past five years.