{"title":"基于帧级混合参数的移动视频服务无参考视频质量评估","authors":"B. Wei, Yuan Zhang","doi":"10.1109/COMPCOMM.2016.7924749","DOIUrl":null,"url":null,"abstract":"No-reference video quality assessment can provide essential information for video service provides to improve user experiences. In this paper, we propose a no-reference video quality assessment method by utilizing the hybrid parameters extracted from compressed video frame. In particular, the proposed method, namely FRAME-FEBP(FRAME-Feature Extraction in Bit stream & Pixel), models the video quality by using both the high-level syntax elements from bit-stream and the statistics calculated on pixels. The experiments show that the proposed method can provide satisfactory results on video quality assessment.","PeriodicalId":210833,"journal":{"name":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"No-reference video quality assessment with frame-level hybrid parameters for mobile video services\",\"authors\":\"B. Wei, Yuan Zhang\",\"doi\":\"10.1109/COMPCOMM.2016.7924749\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"No-reference video quality assessment can provide essential information for video service provides to improve user experiences. In this paper, we propose a no-reference video quality assessment method by utilizing the hybrid parameters extracted from compressed video frame. In particular, the proposed method, namely FRAME-FEBP(FRAME-Feature Extraction in Bit stream & Pixel), models the video quality by using both the high-level syntax elements from bit-stream and the statistics calculated on pixels. The experiments show that the proposed method can provide satisfactory results on video quality assessment.\",\"PeriodicalId\":210833,\"journal\":{\"name\":\"2016 2nd IEEE International Conference on Computer and Communications (ICCC)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 2nd IEEE International Conference on Computer and Communications (ICCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COMPCOMM.2016.7924749\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 2nd IEEE International Conference on Computer and Communications (ICCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPCOMM.2016.7924749","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
无参考视频质量评估可以为视频服务提供商提供必要的信息,改善用户体验。本文提出了一种利用压缩视频帧中提取的混合参数进行无参考视频质量评估的方法。特别地,所提出的方法,即FRAME-FEBP(FRAME-Feature Extraction In Bit stream & Pixel),通过使用来自比特流的高级语法元素和在像素上计算的统计量来建模视频质量。实验结果表明,该方法对视频质量的评估效果令人满意。
No-reference video quality assessment with frame-level hybrid parameters for mobile video services
No-reference video quality assessment can provide essential information for video service provides to improve user experiences. In this paper, we propose a no-reference video quality assessment method by utilizing the hybrid parameters extracted from compressed video frame. In particular, the proposed method, namely FRAME-FEBP(FRAME-Feature Extraction in Bit stream & Pixel), models the video quality by using both the high-level syntax elements from bit-stream and the statistics calculated on pixels. The experiments show that the proposed method can provide satisfactory results on video quality assessment.