QoE-based evaluation model on video streaming service quality
Yun Li Shen, Yitong Liu, Nan Qiao, Lin Sang, Dacheng Yang
Abstract
Yun Li Shen, Yitong Liu, Nan Qiao, Lin Sang, Dacheng Yang
Abstract
The growing demand on video streaming services is the main motive power for video quality assessment. Due to the rapid development of video streaming services, customers are more enjoying higher quality videos, and their perceptions on video service will directly influence the service provider's performance, which makes it significant to study end-users' subjective perception, named as Quality of Experience (QoE), on video streaming for both service providers and end-users. In this paper, a QoE evaluation model is proposed to predict the end-users' perception on video streaming service considering different video content types. This QoE model, named as Video-Mean Opinion Score (VMOS) model, directly focuses on end-users' feeling. Thus, the Key Performance Indicators (KPIs), which can be straightly felt by end-users, are mapped to QoE score without considering the network parameters. The excellent performance of VMOS model for QoE evaluation on video quality has been verified via plenty subjective Mean Opinion Score (MOS) test, which includes 180 video samples with 1280 valid votes. The Pearson Correlation Coefficient between VMOS score and MOS is as high as 0.925, which indicates that this model can evaluate users' perception on video quality with almost the same accuracy as subjective test.
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The growing demand on video streaming services is the main motive power for video quality assessment. Due to the rapid development of video streaming services, customers are more enjoying higher quality videos, and their perceptions on video service will directly influence the service provider's performance, which makes it significant to study end-users' subjective perception, named as Quality of Experience (QoE), on video streaming for both service providers and end-users. In this paper, a QoE evaluation model is proposed to predict the end-users' perception on video streaming service considering different video content types. This QoE model, named as Video-Mean Opinion Score (VMOS) model, directly focuses on end-users' feeling. Thus, the Key Performance Indicators (KPIs), which can be straightly felt by end-users, are mapped to QoE score without considering the network parameters. The excellent performance of VMOS model for QoE evaluation on video quality has been verified via plenty subjective Mean Opinion Score (MOS) test, which includes 180 video samples with 1280 valid votes. The Pearson Correlation Coefficient between VMOS score and MOS is as high as 0.925, which indicates that this model can evaluate users' perception on video quality with almost the same accuracy as subjective test.
Key concepts: Mean opinion score, PEVQ, Computer science, Quality of experience, Subjective video quality, Video quality, Multimedia, Service (business)