{"title":"Estimation of Subjective Video Quality as Feedback to Content Providers","authors":"W. Leister, S. Boudko, Till Halbach","doi":"10.1109/ICSNC.2010.49","DOIUrl":null,"url":null,"abstract":"Concerning video transmission on the Internet, we present a model for estimating the subjective quality from objective measurements at the transmission receivers and on the network. The model reflects the quality degradation subject to parameters like packet loss ratio and bit rate and is calibrated using the results from subjective quality assessments. Besides the model and the calibration, the main achievement of this paper is the model’s validation by implementation in a monitoring tool. It can be used by content and network providers to help swiftly localise the causes of a possibly poor quality of experience (QoE). It also can help content providers make decisions regarding the adjustment of vital parameters, such as bit rate and other error correction mechanisms.","PeriodicalId":152012,"journal":{"name":"2010 Fifth International Conference on Systems and Networks Communications","volume":"55 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Fifth International Conference on Systems and Networks Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSNC.2010.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Concerning video transmission on the Internet, we present a model for estimating the subjective quality from objective measurements at the transmission receivers and on the network. The model reflects the quality degradation subject to parameters like packet loss ratio and bit rate and is calibrated using the results from subjective quality assessments. Besides the model and the calibration, the main achievement of this paper is the model’s validation by implementation in a monitoring tool. It can be used by content and network providers to help swiftly localise the causes of a possibly poor quality of experience (QoE). It also can help content providers make decisions regarding the adjustment of vital parameters, such as bit rate and other error correction mechanisms.