Towards High Resolution Video Quality Assessment in the Crowd

Abstract

Assessing high resolution video quality is usually performed using controlled, defined, and standardized lab tests. This method of acquiring human ratings in a lab environment is time-consuming and may also not reflect the typical viewing conditions. To overcome these disadvantages, crowd testing paradigms have been used for assessing video quality in general. Crowdsourcing-based tests enable a more diverse set of participants and also use a realistic hardware setup and viewing environment of typical users. However, obtaining valid ratings for high-resolution video quality poses several problems. Example issues are that streaming of such high-bandwidth content may not be feasible for some users, or that crowd participants lack an appropriate, high-resolution display device. In this paper, we propose a method to overcome such problems and conduct a crowd test using for higher resolution content by using a 540 p cutout from the center of the original 2160p video. To this aim, we use the videos from Test#1 of the publicly available dataset AVT-VQDB-UHD-1, which contains videos up to a resolution of UHD-1. The quality-labels available from that lab test allow us to compare the results with the crowd test presented in this paper. It is shown that there is a Pearson correlation of 0.96 between the lab and crowd tests and hence such crowd tests can reliably be used for video assessment of higher resolution content. The overall implementation of the crowd test framework and the results are made publicly available for further research and reproducibility1.