{"title":"Do we Really Need No-reference Video Quality Metrics?","authors":"I. Katsavounidis","doi":"10.1145/3423328.3423502","DOIUrl":null,"url":null,"abstract":"Objective video quality metrics are an essential part of modern video processing pipelines, guiding video encoding decisions and encoding recipes, helping adaptive bitrate streaming algorithms make smart decisions and providing system-level monitoring capabilities. We will offer a breakdown of an end-to-end such pipeline, highlighting which types of video quality metrics are deployed in each system component and then focus on the single aspect that makes social videos so much different - and one can argue more difficult - to process: their wildly varying and typically inferior source quality. We will then discuss how no-reference video quality metrics have been typically used to measure user-generated video content quality with limited success and make a case for how the video industry can unite and solve this problem at its root.","PeriodicalId":402203,"journal":{"name":"Proceedings of the 1st Workshop on Quality of Experience (QoE) in Visual Multimedia Applications","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st Workshop on Quality of Experience (QoE) in Visual Multimedia Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3423328.3423502","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
Objective video quality metrics are an essential part of modern video processing pipelines, guiding video encoding decisions and encoding recipes, helping adaptive bitrate streaming algorithms make smart decisions and providing system-level monitoring capabilities. We will offer a breakdown of an end-to-end such pipeline, highlighting which types of video quality metrics are deployed in each system component and then focus on the single aspect that makes social videos so much different - and one can argue more difficult - to process: their wildly varying and typically inferior source quality. We will then discuss how no-reference video quality metrics have been typically used to measure user-generated video content quality with limited success and make a case for how the video industry can unite and solve this problem at its root.