{"title":"An Automated Testbed for Video Quality Optimization over Lossy Networks","authors":"A. Khalifeh, Saifaldeen Al-Rawi, Firas Alabsi","doi":"10.1145/3177404.3177448","DOIUrl":null,"url":null,"abstract":"With the wide adoption of video streaming services and applications, it is important to understand the effect of changing different video quality parameters such as the resolution, frames per second, and the compression rate on the perceived video quality as a function of different network impartments, such as packet loss, delay, bandwidth limitation, etc. To achieve that, an automated testbed that can stream a large number of videos, while automatically varying the aforementioned parameters, under different network impartments and conditions and without the user intervention is proposed, which can lead to better realize how the aforementioned parameters can be optimized, as a function of the network impairments. This realization can in turn lead to propose an optimal video adaptation algorithm that gives the user the best video quality for a certain network conditions, which is of high importance especially in todays congested and lossy networks.","PeriodicalId":133378,"journal":{"name":"Proceedings of the International Conference on Video and Image Processing","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Video and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3177404.3177448","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the wide adoption of video streaming services and applications, it is important to understand the effect of changing different video quality parameters such as the resolution, frames per second, and the compression rate on the perceived video quality as a function of different network impartments, such as packet loss, delay, bandwidth limitation, etc. To achieve that, an automated testbed that can stream a large number of videos, while automatically varying the aforementioned parameters, under different network impartments and conditions and without the user intervention is proposed, which can lead to better realize how the aforementioned parameters can be optimized, as a function of the network impairments. This realization can in turn lead to propose an optimal video adaptation algorithm that gives the user the best video quality for a certain network conditions, which is of high importance especially in todays congested and lossy networks.