  Video dimensions are continuously increasing to provide more realistic and
immersive experiences to global streaming and social media viewers. However,
increments in video parameters such as spatial resolution and frame rate are
inevitably associated with larger data volumes. Transmitting increasingly
voluminous videos through limited bandwidth networks in a perceptually optimal
way is a current challenge affecting billions of viewers. One recent practice
adopted by video service providers is space-time resolution adaptation in
conjunction with video compression. Consequently, it is important to understand
how different levels of space-time subsampling and compression affect the
perceptual quality of videos. Towards making progress in this direction, we
constructed a large new resource, called the ETRI-LIVE Space-Time Subsampled
Video Quality (ETRI-LIVE STSVQ) database, containing 437 videos generated by
applying various levels of combined space-time subsampling and video
compression on 15 diverse video contents. We also conducted a large-scale human
study on the new dataset, collecting about 15,000 subjective judgments of video
quality. We provide a rate-distortion analysis of the collected subjective
scores, enabling us to investigate the perceptual impact of space-time
subsampling at different bit rates. We also evaluated and compared the
performance of leading video quality models on the new database.
