基于神经网络的IP网络视频流质量评估测试平台

Pablo Frank, Jose Incera
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引用次数: 28

摘要

我们介绍了一种模块化的方法,通过使用人工神经网络来评估模拟分组网络中视频流的感知质量。给出了该试验台的具体实现,并讨论了在简单网络配置下的测试结果。我们的工具能够准确地预测人类观众的MOS分数。还介绍了该试验台的其他应用。对于数据分析,我们发现在MPEG-4编解码器中可以控制的通常参数对感知视频质量的影响并不像保护视频流的良好网络设计那样强烈
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A Neural Network Based Test Bed for Evaluating the Quality of Video Streams in IP Networks
We introduce a modular methodology for evaluating the perceived quality of video streams in simulated packet networks through the use of artificial neural networks. One particular implementation of the test bed is presented and the results obtained with it under simple network configurations are discussed. Our tool was able to accurately predict the MOS scores of human viewers. Other applications of the test bed are also presented. For data analysis, we found that the usual parameters that can be controlled in an MPEG-4 codec do not have such a strong influence on the perceived video quality as a good network design that protects the video flows may do
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