Estimating QP and motion vectors in H.264/AVC video from decoded pixels

MiFor '10 Pub Date : 2010-10-29 DOI:10.1145/1877972.1877995
G. Valenzise, M. Tagliasacchi, S. Tubaro
{"title":"Estimating QP and motion vectors in H.264/AVC video from decoded pixels","authors":"G. Valenzise, M. Tagliasacchi, S. Tubaro","doi":"10.1145/1877972.1877995","DOIUrl":null,"url":null,"abstract":"In this paper we present a method for blindly estimating the quantization parameter (QP) and the motion-vectors in H.264/AVC decoded video. We assume that only the decoded pixel values are available. This models pretty well the dissemination over the Internet of user-generated contents, where a video may pass through several coding/processing stages from acquisition to publication and download.\n The proposed technique may be a relevant tool in the forensics field, as it can help to reconstruct the previous history of the digital content, or to provide evidence of tampering.\n Most of the previous work in this direction simply adapts still image forensic approaches to video, but their applicability is in general limited (e.g.\\ they can deal with Intra frames only).\n Conversely, we explicitly take into consideration motion-compensated prediction used by state-of-the-art video codecs such as H.264/AVC to find the QP also for P frames. We show that the so-obtained QPs can be used to estimate the original motion field of the encoder.","PeriodicalId":355677,"journal":{"name":"MiFor '10","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MiFor '10","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1877972.1877995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22

Abstract

In this paper we present a method for blindly estimating the quantization parameter (QP) and the motion-vectors in H.264/AVC decoded video. We assume that only the decoded pixel values are available. This models pretty well the dissemination over the Internet of user-generated contents, where a video may pass through several coding/processing stages from acquisition to publication and download. The proposed technique may be a relevant tool in the forensics field, as it can help to reconstruct the previous history of the digital content, or to provide evidence of tampering. Most of the previous work in this direction simply adapts still image forensic approaches to video, but their applicability is in general limited (e.g.\ they can deal with Intra frames only). Conversely, we explicitly take into consideration motion-compensated prediction used by state-of-the-art video codecs such as H.264/AVC to find the QP also for P frames. We show that the so-obtained QPs can be used to estimate the original motion field of the encoder.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
从解码像素估计H.264/AVC视频的QP和运动向量
本文提出了一种H.264/AVC解码视频中量化参数(QP)和运动矢量的盲估计方法。我们假设只有解码的像素值是可用的。这个模型很好地模拟了互联网上用户生成内容的传播,其中视频可能要经过几个编码/处理阶段,从获取到发布和下载。所提出的技术可能是取证领域的相关工具,因为它可以帮助重建数字内容的以前历史,或提供篡改的证据。在这个方向上的大多数先前的工作只是简单地将静态图像取证方法应用于视频,但它们的适用性通常是有限的(例如,它们只能处理内部帧)。相反,我们明确地考虑到运动补偿预测使用的最先进的视频编解码器,如H.264/AVC,以找到QP也为P帧。我们证明了所得到的QPs可以用来估计编码器的原始运动场。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
When multimedia meets surveillance and forensics in people security Privacy preserving video surveillance using pedestrian tracking mechanism A game-theoretic system security design for the visible watermarking Videntifier" Forensic: large-scale video identification in practice Imputing human descriptions in semantic biometrics
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1