Modern video streaming services require quality assurance of the presented audiovisual material. Quality assurance mechanisms allow streaming platforms to provide quality levels that are considered sufficient to yield user satisfaction, with the least possible amount of data transferred. A variety of measures and approaches have been developed to control video quality, e.g., by adapting it to network conditions. These include objective matrices of the quality and thresholds identified by means of subjective perceptual judgments. The former group of matrices has recently gained the attention of (multi)media researchers. They call this area of study ``Quality of Experience'' (QoE). In this paper, we present a review of QoE's theoretical models together with a discussion of their properties and implications for the field. We argue that most of them represent the bottom-up approach to modeling. Such models focus on describing as many variables as possible, but with a limited ability to investigate the causal relationship between them; therefore, the applicability of the findings in practice is limited. To advance the field, we therefore propose a structural, top-down model of video QoE that describes causal relationships among variables. We hope that our framework will facilitate designing comparable experiments in the domain.

翻译：现代视频流服务需要对呈现的视听材料进行质量保证。质量保证机制允许流媒体平台在传输最少数据量的前提下，提供足以满足用户满意度的质量水平。目前已开发出多种控制视频质量的措施与方法，例如根据网络条件动态调整视频质量。这些方法包括客观质量指标以及通过主观感知判断确定的阈值。前者近年来引起了（多）媒体研究人员的关注，他们将这一研究领域称为"体验质量"（QoE）。本文回顾了体验质量的理论模型，并讨论了其特性及对该领域的影响。我们认为，大多数模型代表了自下而上的建模方法。这类模型侧重于描述尽可能多的变量，但研究变量间因果关系的能力有限，因此研究结果在实践中的适用性受限。为推动该领域发展，我们提出了一种结构化的自上而下视频体验质量模型，该模型描述了变量间的因果关系。希望我们的框架能促进该领域内可比实验的设计。