Intel Corporation, Chandler, AZ 85226, USA.
IEEE Trans Image Process. 2010 Jun;19(6):1427-41. doi: 10.1109/TIP.2010.2042111. Epub 2010 Feb 2.
We present the results of a recent large-scale subjective study of video quality on a collection of videos distorted by a variety of application-relevant processes. Methods to assess the visual quality of digital videos as perceived by human observers are becoming increasingly important, due to the large number of applications that target humans as the end users of video. Owing to the many approaches to video quality assessment (VQA) that are being developed, there is a need for a diverse independent public database of distorted videos and subjective scores that is freely available. The resulting Laboratory for Image and Video Engineering (LIVE) Video Quality Database contains 150 distorted videos (obtained from ten uncompressed reference videos of natural scenes) that were created using four different commonly encountered distortion types. Each video was assessed by 38 human subjects, and the difference mean opinion scores (DMOS) were recorded. We also evaluated the performance of several state-of-the-art, publicly available full-reference VQA algorithms on the new database. A statistical evaluation of the relative performance of these algorithms is also presented. The database has a dedicated web presence that will be maintained as long as it remains relevant and the data is available online.
我们呈现了最近一项大规模主观研究的结果,该研究针对的是一系列受到各种应用相关过程干扰的视频。由于针对人类作为视频最终用户的应用程序数量众多,因此评估人类观察者感知的数字视频视觉质量的方法变得越来越重要。由于正在开发许多视频质量评估(VQA)方法,因此需要一个多样化的、独立的、公共的、可自由获取的失真视频和主观评分数据库。由此产生的图像和视频工程实验室(LIVE)视频质量数据库包含 150 个失真视频(从十个自然场景的未压缩参考视频中获得),这些视频是使用四种常见的失真类型创建的。每个视频都由 38 个人类主体进行评估,并记录了差异平均意见分数(DMOS)。我们还评估了几种最新的、公开可用的全参考 VQA 算法在新数据库上的性能。还对这些算法的相对性能进行了统计评估。该数据库有一个专门的网络存在,只要它仍然相关并且数据在线可用,就会一直维护。