This paper proposes a novel method for video quality evaluation based on machine learning technique. The current research deals with the correct interpretation of objective video quality evaluation (Quality of Service – QoS) in relation to subjective end-user perception (Quality of Experience – QoE), typically expressed by mean opinion score (MOS). Our method allows us to interconnect results obtained from video objective and subjective assessment methods in the form of a neural network (computing model inspired by biological neural networks). So far, no unified interpretation scale has been standardized for both approaches, therefore it is difficult to determine the level of end-user satisfaction obtained from the objective assessment. Thus, contribution of the proposed method lies in description of the way to create a hybrid metric that delivers fast and reliable subjective score of perceived video quality for internet television (IPTV) broadcasting companies.

中文翻译：

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基于神经网络的视频质量感知评价新方法

本文提出了一种基于机器学习技术的视频质量评估新方法。当前的研究涉及客观视频质量评估（服务质量– QoS）与主观最终用户感知（体验质量– QoE）的正确解释，通常以平均意见得分（MOS）表示。我们的方法允许我们以神经网络（受生物神经网络启发的计算模型）的形式互连从视频客观和主观评估方法获得的结果。到目前为止，还没有针对这两种方法的统一解释量表进行标准化，因此很难确定从客观评估中获得的最终用户满意度水平。因此，