Study of Subjective and Objective Quality Assessment of Mobile Cloud Gaming Videos
Autor: | Saha, Avinab, Chen, Yu-Chih, Davis, Chase, Qiu, Bo, Wang, Xiaoming, Gowda, Rahul, Katsavounidis, Ioannis, Bovik, Alan C. |
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Rok vydání: | 2023 |
Předmět: | |
Druh dokumentu: | Working Paper |
DOI: | 10.1109/TIP.2023.3281170 |
Popis: | We present the outcomes of a recent large-scale subjective study of Mobile Cloud Gaming Video Quality Assessment (MCG-VQA) on a diverse set of gaming videos. Rapid advancements in cloud services, faster video encoding technologies, and increased access to high-speed, low-latency wireless internet have all contributed to the exponential growth of the Mobile Cloud Gaming industry. Consequently, the development of methods to assess the quality of real-time video feeds to end-users of cloud gaming platforms has become increasingly important. However, due to the lack of a large-scale public Mobile Cloud Gaming Video dataset containing a diverse set of distorted videos with corresponding subjective scores, there has been limited work on the development of MCG-VQA models. Towards accelerating progress towards these goals, we created a new dataset, named the LIVE-Meta Mobile Cloud Gaming (LIVE-Meta-MCG) video quality database, composed of 600 landscape and portrait gaming videos, on which we collected 14,400 subjective quality ratings from an in-lab subjective study. Additionally, to demonstrate the usefulness of the new resource, we benchmarked multiple state-of-the-art VQA algorithms on the database. The new database will be made publicly available on our website: \url{https://live.ece.utexas.edu/research/LIVE-Meta-Mobile-Cloud-Gaming/index.html} Comment: Accepted to IEEE Transactions on Image Processing, 2023. The database will be publicly available by 1st week of July 2023 |
Databáze: | arXiv |
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