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Network video quality assessment method using fuzzy decision tree

机译:基于模糊决策树的网络视频质量评估方法

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摘要

At present the service of network video is increasing rapidly. The video quality of experience is usually defined as user experience. However, the objective quality assessment for network video is unsure but is an urgent need. To improve the objective method, this study proposes an assessment method using a fuzzy decision tree. This work has two parts: (i) It considers different impair factors. Next, the decision tree is built by the set of measured factors from the different network environments. This tree can define the quality of network video, but cannot give the concrete objective scores. (ii) In order to give the accuracy objective scores, all the impair factors of leaf nodes are divided into two groups and inputted to fuzzy logic systems. The outputs are used as the next inputs and inputted into another fuzzy logic system to give the objective score. At last, the performance of the proposed method is tested on network videos with different network environments. At the same time, other methods are compared with it. The experimental results show that this method can get more accurate objective scores. This means the proposed method can improve the objective assessment model.
机译:目前,网络视频服务正在迅速增长。视频体验质量通常被定义为用户体验。然而,对于网络视频的客观质量评估尚不确定,但迫切需要。为了改进客观方法,本研究提出了一种使用模糊决策树的评估方法。这项工作分为两个部分:(i)考虑不同的减值因素。接下来,由来自不同网络环境的一组测量因子构建决策树。这棵树可以定义网络视频的质量,但不能给出具体的客观评分。 (ii)为了给出准确度的客观评分,将所有叶节点的损害因素分为两组,并输入到模糊逻辑系统中。这些输出用作下一个输入,并输入到另一个模糊逻辑系统中以给出客观分数。最后,在不同网络环境下的网络视频上测试了该方法的性能。同时,将其他方法与之比较。实验结果表明,该方法可以获得较准确的客观得分。这意味着所提出的方法可以改善客观评估模型。

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