Study of Subjective and Objective Quality Assessment of Mobile Cloud
  Gaming Videos
Avinab Saha Yu-Chih Chen Chase Davis Bo Qiu Xiaoming Wang Rahul Gowda Ioannis Katsavounidis Alan C. Bovik
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}