{"title":"Watermarking Video Clips with Workload Information for DVS","authors":"Yicheng Huang, S. Chakraborty, Ye Wang","doi":"10.1109/VLSI.2008.103","DOIUrl":null,"url":null,"abstract":"We present a lightweight scheme for watermarking or annotating video clips with information describing the workload that would be incurred while decoding the clip. This information can be used at run time to scale the operating voltage/frequency of the processor on which the video clip is to be decoded. Our main contribution is a fast, low-cost bitstream analysis technique for estimating the decoding workload of a video clip. Using this technique the workload information can be inserted into a clip while it is being downloaded onto a battery-powered portable device from a desktop computer or a server, for later playback. In contrast to control-theoretic feedback techniques that have been traditionally used for predicting video decoding workload at runtime for dynamic voltage/frequency scaling, we show that our scheme performs better in terms of energy savings and has significantly lower buffer requirements.","PeriodicalId":143886,"journal":{"name":"21st International Conference on VLSI Design (VLSID 2008)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"21st International Conference on VLSI Design (VLSID 2008)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VLSI.2008.103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
We present a lightweight scheme for watermarking or annotating video clips with information describing the workload that would be incurred while decoding the clip. This information can be used at run time to scale the operating voltage/frequency of the processor on which the video clip is to be decoded. Our main contribution is a fast, low-cost bitstream analysis technique for estimating the decoding workload of a video clip. Using this technique the workload information can be inserted into a clip while it is being downloaded onto a battery-powered portable device from a desktop computer or a server, for later playback. In contrast to control-theoretic feedback techniques that have been traditionally used for predicting video decoding workload at runtime for dynamic voltage/frequency scaling, we show that our scheme performs better in terms of energy savings and has significantly lower buffer requirements.