A Large-Scale Subjective Video Quality Database
The MCL joined a collaborative project to build a large-scale subjective video quality database. The database was proposed to boost a major breakthrough in video coding and processing. On one hand, revolutionary ideas rather than fine-tuning patches are highly expected to accommodate increasing video traffic. On the other hand, PSNR has been the dominant distortion metric for many years, but it has also been criticized for not correlating well with perceptual quality. With this database, perceptual coding is promising to lead to numerous R&D opportunities and revolutionary research with machine learning tools.
The database consists of 200 raw sequences with a duration of 5 seconds, encoded by H.264/AVC with fixed QP as bit rate control method. They are available in 5 resolutions from 3840×2160 to 540×360. Around 1000 students participated in the subjective test and it took around 7000 hours to get sufficient samples about 3 JND points. The database will be freely available for downloading for scientific purposes.
The projected was supported by 4 major multimedia companies, Netflix, Huawei, MediaTek, and Samsung. Meanwhile, 6 universities at Shenzhen joined the project, Shenzhen Institutes of Advanced Technology (Chinese Academy of Science), Shenzhen University, Graduate School at Shenzhen (Tsinghua University), Peking University Shenzhen Graduate School, The Chinese University of Hong Kong (Shenzhen), City University of Hong Kong.
We would like to give special thanks to the participating companies, institutes and universities.