面向内容网络环境的视频内容标识方案

doi:10.11959/j.issn.1000-0801.2018182

Abstract

Abstract:

Video fingerprinting technology is a video identification technology proposed for the identification of massive video data.Firstly,the research status of the content network and the main problems that exist were elaborated,especially the problems of content identification.Then design principles of the video content identification scheme were proposed from the video content identification requirements in the content network,and the principles and disadvantages of the existing solutions were analyzed in depth.Finally,a video content identification scheme based on video fingerprinting technology was designed and implemented after analyzing the concept and principle of video fingerprinting technology.The feature was:the two types of video fingerprinting technology in the time domain and frequency domain were integrated.While shortening the time for generating video tags,it also improved the robustness of the overall system.

Key words: content network, content identification, video processing, video fingerprint

CLC Number:

TN919.85

Xun CHEN,Shuai HAN,Shanshan LIU,Xiaolong YANG. Video content identification scheme in content oriented network environment[J]. Telecommunications Science, 2018, 34(6): 53-63.

Figures/Tables 8

References 26

[1]	尹浩, 袁小群, 林闯 ,等. 内容网络服务节点部署理论综述[J]. 计算机学报, 2010,33(9): 1611-1620.
	YIN H , YUAN X Q , LIN C ,et al. The survey of service nodes placement theories for content networks[J]. Chinese Journal of Computers, 2010,33(9): 1611-1620.
[2]	唐霏 . 内容网络中的缓存设计[D]. 成都:电子科技大学, 2013.
	TANG F . Caching design in content network[D]. Chengdu:University of Electronic Science and Technology, 2013.
[3]	胡骞 . 以内容为中心的网络中缓存技术的若干问题研究[D]. 北京:北京邮电大学, 2015.
	HU Q . Research on caching technology in content centric network[D]. Beijing:Beijing University of Posts and Telecommunications, 2015.
[4]	崔现东 . 内容中心网络网内缓存策略研究[D]. 北京:北京邮电大学, 2014.
	CUI X D . Research on caching strategy in content center network[D]. Beijing:Beijing University of Posts and Telecommunications, 2014.
[5]	黄韬, 刘江, 霍如 ,等. 未来网络体系架构研究综述[J]. 通信学报, 2017,35(8): 184-197.
	HUANG T , LIU J , HUO R ,et al. Survey of research on future network architectures[J]. Journal on Communications, 2017,35(8): 184-197.
[6]	刘斌, 汪漪 . 内容中心网络中名字查找技术的研究[J]. 电信科学, 2017,30(9): 10-17.
	LIU B , WANG Y . Research on name lookup in named data networking[J]. Telecommunications Science, 2017,30(9): 10-17.
[7]	张行功, 牛童, 郭宗明 . 未来网络之内容中心网络的挑战和应用[J]. 电信科学, 2017,29(8): 24-31.
	ZHANG X G , NIU T , GUO Z M . Challenge and implementation of content-centric networking[J]. Telecommunications Science, 2017,29(8): 24-31.
[8]	JACOBSON V , SMETTERS D K , THORNTON J D ,et al. Networking named content[C]// The 5th International Conference on Emerging Networking Experiments and Technologies,December 1-4,2009,Rome,Italy. New York:ACM Press, 2009: 1-12.
[9]	ZHANG G , LI Y , LIN T . Caching in information centric networking:a survey[J]. Computer Networks, 2013,57(16): 3128-3141.
[10]	胡骞, 武穆清, 郭嵩 . 以内容为中心的未来通信网络研究综述[J]. 电信科学, 2012,28(9): 74-80.
	HU Q , WU M Q , GUO S . A survey of content-oriented future communication network[J]. Telecommunications Science, 2012,28(9): 74-80.
[11]	雷凯 . 信息中心网络与命名数据网络[M]. 北京: 北京大学出版社, 2015.
	LEI K . Information-centric networking (ICN) and named-data networking (NDN)[M]. Beijing: Peking University PressPress, 2015.
[12]	王大永 . 感知视频指纹算法研究[D]. 上海:上海交通大学, 2012.
	WANG D Y . Research on perceptual video fingerprint algorithm[D]. Shanghai:Shanghai Jiao Tong University, 2012.
[13]	WALFISH M , BALAKRISHNAN H , SHENKER S . Untangling the Web from DNS[C]// NSDI 2004,March 29-31,2004,San Francisco,CA,USA. New York:ACM Press, 2004:17.
[14]	ANAND A , BALACHANDRAN A , AKELLA A ,et al. Enhancing video accessibility and availability using information-bound references[J]. IEEE/ACM Transactions on Networking (TON), 2016,24(2): 1223-1236.
[15]	KIM M J , YOO C , KO Y W . Multimedia file forensics system exploiting file similarity search[J]. Multimedia Tools and Applications, 2017: 1-22.
[16]	NIE X , YIN Y , SUN J ,et al. Comprehensive feature-basedrobust video fingerprinting using tensor model[J]. IEEE Transactions on Multimedia, 2017,19(4): 785-796.
[17]	许涛 . 面向视频管理的指纹特征提取技术研究[D]. 成都:电子科技大学, 2015.
	XU T . Research on fingerprint feature extraction technology for video management[D]. Chengdu:University of Electronic Science and Technology, 2015.
[18]	INDYK P , IYENGAR G , SHIVAKUMAR N . Finding pirated video sequences on the internet[R]. 1999.
[19]	OUALI C , DUMOUCHEL P , GUPTA V . Robust video fingerprints using positions of salient regions[C]// 2017 IEEE International Conference on Acoustics,Speech and Signal Processing (ICASSP),March 5-9,2017,New Orleans,USA. Piscataway:IEEE Press, 2017: 3041-3045.
[20]	庄捷 . 流媒体原理与应用[M]. 北京: 中国广播电视出版社, 2012.
	ZHUANG J . Principle and application of streaming media[M]. Beijing: China Radio and Television Publishing HousePress, 2012.
[21]	LU J , . Video fingerprinting for copy identification:from research to industry applications[C]// Media Forensics and Security.International Society for Optics and Photonics,January 19,2009,San Jose,CA,USA.[S.l.:s.n]. 2009:725402.
[22]	INDYK P , MOTWANI R . Approximate nearest neighbors:towards removing the curse of dimensionality[C]// The 30th Annual ACM Symposium on Theory of Computing,May 24-26,1998,New York,USA. New York:ACM Press, 1998: 604-613.
[23]	HU S , . Efficient video retrieval by locality sensitive hashing[C]// IEEE 2005 International Conference on Acoustics,Speech,and Signal Processing (ICASSP’05),March 18-23,2005,Philadelphia,Pennsylvania,USA. Piscataway:IEEE Press, 2005: 449-452.
[24]	ESMAEILI M M , FATOURECHI M , WARD R K . A robust and fast video copy detection system using content-based fingerprinting[J]. IEEE Transactions on Information Forensics and Security, 2011,6(1): 213-226.
[25]	OOSTVEEN J , KALKER T , HAITSMA J . Feature extraction and a database strategy for video fingerprinting[M]. Berlin: SpringerPress, 2002: 117-128.
[26]	COSKUN B , SANKUR B . Robust video hash extraction[C]// 2004 12th European Signal Processing Conference,Sept 6,2004,Vienna,Austria. Piscataway:IEEE Press, 2004: 2295-2298.

Metrics

Recommended 0

No Suggested Reading articles found!

Video content identification scheme in content oriented network environment

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 26

Related Articles 1

Metrics

Recommended 0