A packet-layer video quality assessment model with spatiotemporal complexity estimation

A packet-layer video quality assessment (VQA) model is a lightweight model that predicts the video quality impacted by network conditions and coding configuration for application scenarios such as video system planning and in-service video quality monitoring. It is under standardization in ITU-T Study Group (SG) 12. In this article, we first differentiate the requirements for VQA model from the two application scenarios, and state the argument that the dataset for evaluating the quality monitoring model should be more challenging than that for system planning model. Correspondingly, different criteria and approaches are used for constructing the test datasets, for system planning (dataset-1) and for video quality monitoring (dataset-2), respectively. Further, we propose a novel video quality monitoring model by estimating the spatiotemporal complexity of video content. The model takes into account the interactions among content features, the error concealment effectiveness, and error propagation effects. Experiment results demonstrate that the proposed model achieves robust performance improvement compared with the existing peer VQA metrics on both dataset-1 and dataset-2. It is noted that on the more challenging dataset-2 for video quality monitoring, we obtain a large increase in Pearson correlation from 0.75 to 0.92 and a decrease in the modified RMSE from 0.41 to 0.19.