.png){kind=icon}
返回
Parametric Quality-Estimation Model for Adaptive-Bitrate-Streaming Services
.png){kind=icon}
PRE
AI
DOI：10.1109/TMM.2017.2669859.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The use of adaptive-bitrate-streaming services over networks has been increasing in recent years. The quality of adaptive-bitrate-streaming services is primarily affected by the video resolution, the audio and video bitrate, bitrate adaptation, stalling due to a lack of playout buffer, and the content length. Therefore, service providers should monitor quality in real time to confirm the normality of their services. To accurately monitor quality, a model that can be used for quality estimation should be developed. To develop such a model, we first conducted extensive subjective quality assessment tests. We then developed a model using the subjective data obtained in the tests. Finally, we verified the performance of the proposed model by applying it to unknown datasets (different from the training datasets used to develop the model) and confirmed its high quality-estimation accuracy.
Keyword:
Adaptive-bitrate streaming
compression
monitoring
quality
stalling
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.7
论文数:
4.5K
被引数:
2.4W
机构
暂无机构信息
引用论文
Cluster synchronization and rhythm dynamics in a complex neuronal network with chemical synapses
PREAI
分享收藏
Demonstration and Diagnostic Significance of Pro-Gastrin-Releasing Peptide in Medullary Thyroid Carcinoma.png)
Oncology
OncologyIF0
PREAI
分享收藏分享收藏
查看更多内容