基于神经网络的无参考视频质量体验度量

Amal Sufiuh Ajrash, R. F. Ghani, L. Al-Jobouri
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引用次数: 2

摘要

近年来,信息技术有了巨大的发展,这使得通过互联网快速访问不同类型的数据成为可能,其中一种数据类型是视频,用户可以直接在线观看视频。本文提供了一种视频流QoE评价指标,该指标不需要参考视频的任何信息。该系统从视频中提取特征数,用于训练神经网络并最终评估QoE值。使用10倍交叉验证验证训练模型的预测。该系统在SRCC指标上的最佳相关结果为0.95。
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ANN based Measurement for No-Reference Video Quality of Experience Metric
In recent years, there has been a tremendous development in information technology, which has led to the possibility of fast access to different data types over the Internet, one of the data type is video and the ability for the user to watch video directly online. This paper provides a video streaming QoE evaluation metric that does not require any information on the reference video. The proposed system extract numbers of features from videos that are used to train the neural network and finally evaluate the QoE value. Verify training models prediction using 10-fold cross-validation. The proposed system had the best correlation result 0.95 in SRCC metric.
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