公开(公告)号：US09838680B2

公开(公告)日：2017-12-05

申请号：US15185231

申请日：2016-06-17

Applicant: Huawei Technologies Co., Ltd.

Inventor： Xiaolin Deng ,  Guanglin Han ,  Zesong Fei ,  Wei Bai

IPC: H04N17/00 ,  H04L29/06

CPC classification number: H04N17/004 ,  H04L65/80

Abstract: The method includes: processing a PSNR of each segment of each sample video, determining an ePSNR predictive model according to preset parameters obtained after processing and mean opinion scores of all sample videos, and determining an enhanced mean opinion score eMOS predictive model according to the predictive model. Then, for any video that needs to be evaluated, QoE of the video that needs to be evaluated may be determined according to only the enhanced MOS predictive model and an ePSNR determined according to the ePSNR predictive model. In comparison with a prior-art method for determining QoE in which only a mean value of PERNs of all frames is considered, in this process of measuring quality of experience of a mobile video service, as many as factors that affect a PSNR of a video are considered. Therefore, accurate measurement of quality of experience of an HAS video service can be implemented.

公开(公告)号：US20160295210A1

公开(公告)日：2016-10-06

申请号：US15185231

申请日：2016-06-17

Applicant: Huawei Technologies Co., Ltd.

Inventor： Xiaolin Deng ,  Guanglin Han ,  Zesong Fei ,  Wei Bai

IPC: H04N17/00 ,  H04L29/06

CPC classification number: H04N17/004 ,  H04L65/80

Abstract: The method includes: processing a PSNR of each segment of each sample video, determining an ePSNR predictive model according to preset parameters obtained after processing and mean opinion scores of all sample videos, and determining an enhanced mean opinion score eMOS predictive model according to the predictive model. Then, for any video that needs to be evaluated, QoE of the video that needs to be evaluated may be determined according to only the enhanced MOS predictive model and an ePSNR determined according to the ePSNR predictive model. In comparison with a prior-art method for determining QoE in which only a mean value of PERNs of all frames is considered, in this process of measuring quality of experience of a mobile video service, as many as factors that affect a PSNR of a video are considered. Therefore, accurate measurement of quality of experience of an HAS video service can be implemented.

Abstract translation: 该方法包括：处理每个采样视频的每个片段的PSNR，根据处理后获得的预设参数和所有样本视频的平均意见得分确定ePSNR预测模型，并根据预测值确定增强的平均意见分数eMOS预测模型 模型。 然后，对于需要评估的任何视频，可以仅根据增强的MOS预测模型和根据ePSNR预测模型确定的ePSNR来确定需要评估的视频的QoE。 与用于确定仅考虑所有帧的PERN的平均值的QoE的现有技术方法相比，在测量移动视频服务的体验质量的过程中，影响视频的PSNR的因素一样多 被考虑。 因此，可以实现对HAS视频服务的体验质量的准确测量。