In this article, we make the first attempt to study the subjective and objective quality assessment for the screen content video s (SCVs). For that, we construct the first large-scale video quality assessment (VQA) database specifically for the SCVs, called the screen content video database (SCVD). This SCVD provides 16 reference SCVs, 800 distorted SCVs, and their corresponding subjective scores, and it is made publicly available for research usage. The distorted SCVs are generated from each reference SCV with 10 distortion types and 5 degradation levels for each distortion type. Each distorted SCV is rated by at least 32 subjects in the subjective test. Furthermore, we propose the first full-reference VQA model for the SCVs, called the spatiotemporal Gabor feature tensor-based model (SGFTM), to objectively evaluate the perceptual quality of the distorted SCVs. This is motivated by the observation that 3D-Gabor filter can well stimulate the visual functions of the human visual system (HVS) on perceiving videos, being more sensitive to the edge and motion information that are often-encountered in the SCVs. Specifically, the proposed SGFTM exploits 3D-Gabor filter to individually extract the spatiotemporal Gabor feature tensors from the reference and distorted SCVs, followed by measuring their similarities and later combining them together through the developed spatiotemporal feature tensor pooling strategy to obtain the final SGFTM score. Experimental results on SCVD have shown that the proposed SGFTM yields a high consistency on the subjective perception of SCV quality and consistently outperforms multiple classical and state-of-the-art image/video quality assessment models.

中文翻译：

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屏幕内容视频质量评估：主观和客观研究。

在本文中，我们进行了首次尝试来研究主观和客观质量评估的内容。 屏幕内容视频 s（SCV）。为此，我们构建了第一个大规模视频质量评估 （VQA）数据库专门用于SCV，称为 屏幕内容视频数据库（SCVD）。该SCVD提供了16个参考SCV，800个失真的SCV及其相应的主观评分，并且已公开提供给研究使用。从每个参考SCV生成失真的SCV，这些SCV具有10种失真类型和每种失真类型5种降级级别。在主观测试中，至少32位受试者对每个扭曲的SCV进行了评级。此外，我们为SCV提出了第一个全参考VQA模型，称为时空Gabor特征张量模型（SGFTM），以客观评估失真SCV的感知质量。这是由于观察到3D-Gabor滤镜可以很好地刺激眼镜的视觉功能而引起的。人类视觉系统（HVS）感知视频，对SCV中经常遇到的边缘和运动信息更加敏感。具体而言，拟议的SGFTM利用3D-Gabor滤波器从参考SCV和失真SCV中分别提取时空Gabor特征张量，然后测量它们的相似性，然后通过开发的时空特征张量合并策略将它们组合在一起，以获得最终的SGFTM分数。在SCVD上的实验结果表明，提出的SGFTM在SCV质量的主观感知上具有很高的一致性，并且始终优于多种经典和最新的图像/视频质量评估模型。