{"title":"DENESTO:一个视频解码能量估计和可视化工具","authors":"Matthias Kränzler, Christian Herglotz, A. Kaup","doi":"10.1109/VCIP49819.2020.9301877","DOIUrl":null,"url":null,"abstract":"In previous research, it is shown that the decoding energy demand of several video codecs can be estimated accurately by using bit stream feature-based models. Therefore, we show in this paper that the visualization with the Decoding Energy Estimation Tool (DENESTO) can help to improve the understanding of the energy demand of the decoder.","PeriodicalId":431880,"journal":{"name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"DENESTO: A Tool for Video Decoding Energy Estimation and Visualization\",\"authors\":\"Matthias Kränzler, Christian Herglotz, A. Kaup\",\"doi\":\"10.1109/VCIP49819.2020.9301877\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In previous research, it is shown that the decoding energy demand of several video codecs can be estimated accurately by using bit stream feature-based models. Therefore, we show in this paper that the visualization with the Decoding Energy Estimation Tool (DENESTO) can help to improve the understanding of the energy demand of the decoder.\",\"PeriodicalId\":431880,\"journal\":{\"name\":\"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VCIP49819.2020.9301877\",\"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 IEEE International Conference on Visual Communications and Image Processing (VCIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VCIP49819.2020.9301877","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DENESTO: A Tool for Video Decoding Energy Estimation and Visualization
In previous research, it is shown that the decoding energy demand of several video codecs can be estimated accurately by using bit stream feature-based models. Therefore, we show in this paper that the visualization with the Decoding Energy Estimation Tool (DENESTO) can help to improve the understanding of the energy demand of the decoder.
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