2020/02/27 by Yim, Joong Gon, Wang, Yilin, Birkbeck, Neil +1 · 2 citations
#FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Multimedia (cs.MM) #electronic engineering #information engineering
paper · doi:10.48550/arxiv.2002.12275
Due to the scale of social video sharing, User Generated Content (UGC) is getting more attention from academia and industry. To facilitate compression-related research on UGC, YouTube has released a large-scale dataset. The initial dataset only provided videos, limiting its use in quality assessment. We used a crowd-sourcing platform to collect subjective quality scores for this dataset. We analyzed the distribution of Mean Opinion Score (MOS) in various dimensions, and investigated some fundamental questions in video quality assessment, like the correlation between full video MOS and corresponding chunk MOS, and the influence of chunk variation in quality score aggregation.