With the rapid growth of Internet video data amounts and types, a unified Video Quality Assessment (VQA) is needed to inspire video communication with perceptual quality. To meet the real-time and universal requirements in providing such inspiration, this study proposes a VQA model from a classification of User Generated Content (UGC), Professionally Generated Content (PGC), and Occupationally Generated Content (OGC). In the time domain, this study utilizes non-uniform sampling, as each content type has varying temporal importance based on its perceptual quality. In the spatial domain, centralized downsampling is performed before the VQA process by utilizing a patch splicing/sampling mechanism to lower complexity for real-time assessment. The experimental results demonstrate that the proposed method achieves a median correlation of $0.7$ while limiting the computation time below 5s for three content types, which ensures that the communication experience of UGC, PGC, and OGC can be optimized altogether.

翻译：随着互联网视频数据数量与类型的快速增长，亟需一种统一的视频质量评估（VQA）模型，以基于感知质量优化视频通信。为满足实时性与通用性要求，本研究基于用户生成内容（UGC）、专业生成内容（PGC）与职业生成内容（OGC）的分类，提出一种VQA模型。在时域上，本研究采用非均匀采样，因为不同内容类型基于其感知质量具有不同的时间重要性。在空域上，在VQA处理前通过补丁拼接/采样机制执行集中下采样，以降低实时评估的复杂度。实验结果表明，所提方法在将三类内容的计算时间限制在5秒以内的同时，实现了中位数相关系数$0.7$，从而确保UGC、PGC与OGC的通信体验可得到整体优化。