Mustafa Othman, Ken Chen, Anissa Zergaïnoh-Mokraoui
{"title":"基于客观视觉质量评价的DASH视频流qos感知适应机制研究","authors":"Mustafa Othman, Ken Chen, Anissa Zergaïnoh-Mokraoui","doi":"10.23919/spa50552.2020.9241250","DOIUrl":null,"url":null,"abstract":"Dynamic Adaptive Streaming over HTTP (DASH) is a largely used video streaming technique. One key point is its adaptation mechanism which resides at the client’s side. This allows various context-aware adaptation strategies in order to optimize the overall Quality of Experience (QoE) of the video streaming. In this paper, we present a study on an adaptation mechanism which uses an objective visual quality assessment, namely the Structural Similarity Index Measurement (SSIM) metric, as a key criterion for adaptation. More specifically, the SSIM helps to maximize the effective use of the available bandwidth, in the sense that we adopt a higher bitrate not only because it is allowed by network conditions, but also because it does bring a significant visual quality improvement (measured through SSIM metric). In this way, an upgrade in bandwidth consumption will be allowed only if there is a real contribution to visual quality. This study has been tested through a series of experimental results obtained with several strategies for the choice of the threshold value. Our tests are all based on real mobile-network traffic traces and real video sequences.","PeriodicalId":157578,"journal":{"name":"2020 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Study of QoE-Aware Adaptation Mechanism for DASH Video Streaming based on Objective Visual Quality Assessment\",\"authors\":\"Mustafa Othman, Ken Chen, Anissa Zergaïnoh-Mokraoui\",\"doi\":\"10.23919/spa50552.2020.9241250\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Dynamic Adaptive Streaming over HTTP (DASH) is a largely used video streaming technique. One key point is its adaptation mechanism which resides at the client’s side. This allows various context-aware adaptation strategies in order to optimize the overall Quality of Experience (QoE) of the video streaming. In this paper, we present a study on an adaptation mechanism which uses an objective visual quality assessment, namely the Structural Similarity Index Measurement (SSIM) metric, as a key criterion for adaptation. More specifically, the SSIM helps to maximize the effective use of the available bandwidth, in the sense that we adopt a higher bitrate not only because it is allowed by network conditions, but also because it does bring a significant visual quality improvement (measured through SSIM metric). In this way, an upgrade in bandwidth consumption will be allowed only if there is a real contribution to visual quality. This study has been tested through a series of experimental results obtained with several strategies for the choice of the threshold value. Our tests are all based on real mobile-network traffic traces and real video sequences.\",\"PeriodicalId\":157578,\"journal\":{\"name\":\"2020 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/spa50552.2020.9241250\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/spa50552.2020.9241250","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Study of QoE-Aware Adaptation Mechanism for DASH Video Streaming based on Objective Visual Quality Assessment
Dynamic Adaptive Streaming over HTTP (DASH) is a largely used video streaming technique. One key point is its adaptation mechanism which resides at the client’s side. This allows various context-aware adaptation strategies in order to optimize the overall Quality of Experience (QoE) of the video streaming. In this paper, we present a study on an adaptation mechanism which uses an objective visual quality assessment, namely the Structural Similarity Index Measurement (SSIM) metric, as a key criterion for adaptation. More specifically, the SSIM helps to maximize the effective use of the available bandwidth, in the sense that we adopt a higher bitrate not only because it is allowed by network conditions, but also because it does bring a significant visual quality improvement (measured through SSIM metric). In this way, an upgrade in bandwidth consumption will be allowed only if there is a real contribution to visual quality. This study has been tested through a series of experimental results obtained with several strategies for the choice of the threshold value. Our tests are all based on real mobile-network traffic traces and real video sequences.