On Evaluating Perceptual Quality of Online User-Generated Videos
This addresses the challenge of designing better video-sharing services for users, but it appears incremental as it focuses on analysis and discussion without introducing new methods.
The paper tackled the problem of evaluating perceptual quality for online user-generated videos by analyzing viewer perception patterns with graph analysis and testing existing objective metrics and metadata for quality estimation, but did not report concrete numerical results.
This paper deals with the issue of the perceptual quality evaluation of user-generated videos shared online, which is an important step toward designing video-sharing services that maximize users' satisfaction in terms of quality. We first analyze viewers' quality perception patterns by applying graph analysis techniques to subjective rating data. We then examine the performance of existing state-of-the-art objective metrics for the quality estimation of user-generated videos. In addition, we investigate the feasibility of metadata accompanied with videos in online video-sharing services for quality estimation. Finally, various issues in the quality assessment of online user-generated videos are discussed, including difficulties and opportunities.