YOUTUBE UGC DATASET FOR VIDEO COMPRESSION RESEARCH
Abstract
User Generated Contents (UGCs) become more and more popular in today’s video sharing applications. However, there are few public UGC data available for video compression and quality assessment research. In this paper, a large scale UGC dataset is introduced, which is sampled from millions of YouTube videos and covers most popular categories like Gaming, Sports, and HDR. Besides a novel sampling method based on features extracted from transcoding, challenges for UGC compression and quality evaluation are also addressed. We also released three no reference quality metrics for the UGC dataset, which overcome certain shortcomings of traditional reference metrics on UGCs.
Research Areas
