  In modern-era video streaming systems, videos are streamed and displayed on a
wide range of devices. Such devices vary from large-screen UHD and HDTVs to
medium-screen Desktop PCs and Laptops to smaller-screen devices such as mobile
phones and tablets. It is well known that a video is perceived differently when
displayed on different devices. The viewing experience for a particular video
on smaller screen devices such as smartphones and tablets, which have high
pixel density, will be different with respect to the case where the same video
is played on a large screen device such as a TV or PC monitor. Being able to
model such relative differences in perception effectively can help in the
design of better quality metrics and in the design of more efficient and
optimized encoding profiles, leading to lower storage, encoding, and
transmission costs. This paper presents a new, open-source dataset consisting
of subjective ratings for various encoded video sequences of different
resolutions and bitrates (quality) when viewed on three devices of varying
screen sizes: TV, Tablet, and Mobile. Along with the subjective scores, an
evaluation of some of the most famous and commonly used open-source objective
quality metrics is also presented. It is observed that the performance of the
metrics varies a lot across different device types, with the recently
standardized ITU-T P.1204.3 Model, on average, outperforming their
full-reference counterparts. The dataset consisting of the videos, along with
their subjective and objective scores, is available freely on Github at
https://github.com/NabajeetBarman/Multiscreen-Dataset.
