Point cloud video has been widely used by augmented reality (AR) and virtual reality (VR) applications as it allows users to have an immersive experience of six degrees of freedom (6DoFs). Yet there is still a lack of research on quality of experience (QoE) model of point cloud video streaming, which cannot provide optimization metric for streaming systems. Besides, position and color information contained in each pixel of point cloud video, and viewport distance effect caused by 6DoFs viewing procedure make the traditional objective quality evaluation metric cannot be directly used in point cloud video streaming system. In this paper we first analyze the subjective and objective factors related to QoE model. Then an experimental system to simulate point cloud video streaming is setup and detailed subjective quality evaluation experiments are carried out. Based on collected mean opinion score (MOS) data, we propose a QoE model for point cloud video streaming. We also verify the model by actual subjective scoring, and the results show that the proposed QoE model can accurately reflect users' visual perception. We also make the experimental database public to promote the QoE research of point cloud video streaming.
翻译:通过扩大现实(AR)和虚拟现实(VR)应用程序,云点视频被广泛使用,因为它使用户能够对六度自由(6DoFs)有初步体验。然而,对点云视频流的经验质量(QoE)模型的研究仍然缺乏,这种模型无法为流流系统提供最佳衡量标准。此外,每个点云视频像素中包含的位置和颜色信息,以及6DoFs查看程序造成的视视像传送距离效应,使得传统的客观质量评估标准无法直接用于点云视频流系统。在本文中,我们首先分析与QoE模型有关的主观和客观因素。随后,我们设置了一个模拟点云视频流的实验系统,并进行了详细的主观质量评估实验试验。根据收集到的平均评分数据,我们提出了点云流视频流的QoE模型。我们还通过实际的主观评分来验证模型,结果显示,拟议的QoE模型能够准确反映用户的视觉认知。我们还将实验数据库公诸于众,以促进点云流视频流的QoE研究。