The research of OTT video quality assessment method

Over the top (OTT) video streaming is widely deployed to deliver stored media. But, the OTT video quality assessment method is uncertain. In this paper, we introduce three application metrics of OTT video quality, including initial buffering time, mean re-buffering duration, and re-buffering frequency. We find the transmission control protocol (TCP) throughput can influence the application metrics; then, we improve the TCP model and forecast the TCP throughput more accuracy. Next, we give experiments to change the network environment and test the OTT video. Our ultimate goal is to characterize the correlation between the application metrics and user quality of experience using simplified fuzzy inference system. Firstly, the nonlinear support vector machine is used to divide the application metrics into different categories. Secondly, the different categories of fuzzy rules are designed to infer the objective scores. The proposed objective model can reduce the calculation steps effectively and improve the similarity. Lastly, the existing assessment methods are compared with it, the experimental results show that the method accords closely with human subjective judgment.