期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

一种新的鲁棒性视频复制检测算法 被引量：1

A New Video Copy Detection Algorithm of High Robustness
在线阅读 下载PDF
导出
摘要 针对现有的视频复制检测方法中存在的计算量大、鲁棒性差等问题,提出了一种新的视频复制检测算法.算法采用视频时序特征曲线来描述视频内容,将每帧图像基于信息熵自动分割成若干个子块,提取各个子块的时序特征曲线作为表征视频内容的特征值.在相似性匹配时,采用鲁棒性的相似性匹配算法,实验结果证明了算法的有效性和鲁棒性. To solve the problems of high computation and low robustness that exist in present video copy detection methods,a new video copy detection method is proposed.This algorithm uses spatio-temporal feature curves of the video to describe the video content.Each frame in the video is divided into several blocks according to the entropy in it and each block＇s spatio-temporal feature curves are extracted to serve as descriptors of its content.A robust matching method is adopted to match the two videos＇ feature curves.The experiments show the effectiveness and robustness of the algorithm.
作者 陈秀新 贾克斌 邓智? 庄新月
机构地区 北京工业大学电子信息与控制工程学院 北京工商大学计算机与信息工程学院
出处 《北京工业大学学报》 EI CAS CSCD 北大核心 2011年第5期691-696,共6页 Journal of Beijing University of Technology
基金 国家自然科学基金资助项目(60672050)
关键词 版权保护 视频复制检测 时序特征曲线 信息检索 copy protection video copy detection spatio-temporal feature information retrieval
分类号 TN911.73 [电子电信—通信与信息系统]
作者简介 陈秀新（1979-），女，山东陵县人，博士研究生．
  • 相关文献

参考文献13

  • 1王炜,徐玮,熊志辉,张茂军.基于模糊直方图的两阶段相似视频的自动鉴别和检索[J].小型微型计算机系统,2007,28(8):1477-1481. 被引量：1
  • 2赵志诚,蔡安妮.基于全局运动的视频检索方案[J].北京邮电大学学报,2006,29(4):18-23. 被引量：2
  • 3SUDHIR G LEE J C M. Video annotation by motion interpretation using optical flow streams [ J ]. Journal of Visual Communication and Image Representation, 1996, 7.-354-365.
  • 4KIM C. Ordinal measure of DCT coefficients for image correspondence and its application to copy detection[ C ] //Proceedings of the SPIE Storage and Retrieval for Media Databases 2003. Santa Clara: SPIE-International Society for Optical Engine, 2003 : 199-210.
  • 5KAHNG A, KIROVSKI D, MANTIK S. Copy detection for intellectual property protection of VLSI design[ C] //Proceedings of the Conference on Computer-Aided Design 1999. California: IEEE Standards Office, 1999: 600-604.
  • 6PICKERING M J, RUGER S. Evaluation of key frame-based retrieval techniques for video[ J]. Computer Vision and Image Understanding, 2003, 92 ( 2/3 ) : 217-235.
  • 7SWAIN M, BALLARD D. Color indexing[ J]. International Journal of Computer Vision, 1991, 7(1) : 11-32.
  • 8HAMPAPUR A, HYUN K H, BOLLE R M. Comparison of sequence matching techniques for video copy detection [ C ]// Proceedings of the Storage and Retrieval for Media Databases, California: SPIE-Intemational Society for Optical Engine, 2002: 194-201.
  • 9HSU W, CHUA T S, PUNG H K. An integrated color-spatial approach to content-based image retrieval[ C ]//Proceedings of the ACM Multimedia. San Francisco: ACM Press, 1995: 305-313.
  • 10SU C W, LIAO H M, TYAN H R, et al. Motion flow-based video retrieval[ J]. IEEE Transactions on Multimedia, 2007, 9 (6) : 1193-1201.

二级参考文献30

  • 1NAPHADE M R, BASU S, SMITH J R. A statistical modeling approach to content based video retrieval[J]. ProceedingsInternational Conference on Pattern Recognition, 2002, 16(2): 953-956.
  • 2Al-OMARI F A, Al-JARRAH M A. Query by image and video content: a colored-based stochastic model approach[J]. Data & Knowledge Engineering, 2005, 52(3): 313-332.
  • 3PICKERING M J, RUGER S. Evaluation of key frame-based retrieval techniques for video[J]. Computer Vision and Image Understanding, 2003, 92(2-3) :217-235.
  • 4HAMPAPUR A, BOLLE R. Comparison of sequence matching techniques for video copy detection[C]//Proc, of Conf. on Storage and Retrieval for Media Databases. San Jose, USA: SPIE, 2002: 194-201.
  • 5OOSTVEEN J, KALKER T, HAITSMA J. Feature extraction and a database strategy for video fingerprinting[C] //Proc. of Int. Conf. on Visual Information and Information Systems. London: Springer-Verlag, 2002 : 117-128.
  • 6AGHBARI Z, KANEKO K, MAKINOUCHI A. VST-model: a uniform topological modeling of the visual-spatio-temporal video features[C]//Proceedings IEEE International Conference on Multimedia Computing and Systems. Japan: IEEE CNF, 1999, 2:163-168.
  • 7LIY, WEN C L, XIE Z, et al. Synchronization of batch trajectory based on multi-scale dynamic time warping[C] // International Conference on Machine Learning and Cybernetics. Xi'an: IEEE CNF, 2003, 4: 2403-2408.
  • 8LIAN N X, TAN Y P, CHAN K L. Efficient video retrieval using shot clustering and alignment [ C] // Proc. of the 4th International Conference on Information, Communications&Signal and Pacific-Rim Conference on Multimedia. Singapore: IEEE CNF, 2003, 3:1801-1805.
  • 9Dagtas S, Ghafoor A. Models for motion-based video indexing and retrieval [J]. IEEE Trans on Image Processing, 2000, 9(1): 88-101.
  • 10Srinivasan M V, Venkatesh S. Qualitative estimation of camera motion parameters from video seque-nces [J]. Pattern Recognit, 1997, 30(4): 593-606.

共引文献5

同被引文献18

  • 1Chen L,Chua T S.A match and tiling approach to content-basedvideo retrieval[C]∥Int.Conf.on Multimedia and Expo.2001:417-420.
  • 2Kashino K,Kurozumi T,Murase H.A quick search method for audio and video signals based on histogram pruning[J].IEEE Transactions on Multimedia,2003,5(3):348-357.
  • 3Chiu C,Wang H.A novel video matching framework for copy detection[C]∥Proc.of the 21th IPPR Conference on Computer Vision,Graphics and Image Processing (CVGIP’2008).2008.
  • 4Myers C S,Rabiner L R.A comparative study of several dynamictime-warping algorithms for connected word recognition[J].The Bell System Technical Journal,1981,60(7):1389-1409.
  • 5Liu F,Dong D G,Miao X,et al.A fast video clip retrieval algorithm based on VA-File[C]∥Electronic Imaging 2004.International Society for Optics and Photonics,2003:167-176.
  • 6Chen T,Jiang S,Chu L,et al.Detection and location of near-duplicate video sub-clips by finding dense subgraphs[C]∥Procee-dings of the 19th ACM international conference on Multimedia.ACM,2011:1173-1176.
  • 7Lowe D G.Distinctive image features from scale-invariant keypoints[J].International journal of computer vision,2004,60(2):91-110.
  • 8Bay H,Tuytelaars T,Van Gool L.Surf:Speeded up robust features[M].Computer Vision-ECCV 2006.Springer Berlin Heidelberg,2006:404-417.
  • 9Rosten E,Drummond T.Machine learning for high-speed corner detection[M]∥Computer Vision-ECCV 2006.Springer Berlin Heidelberg,2006:430-443.
  • 10Calonder M,Lepetit V,Strecha C,et al.BRIEF:binary robustindependent elementary features[M]∥Computer Vision-ECCV 2010.Springer Berlin Heidelberg,2010:778-792.

引证文献1

二级引证文献2

北京工业大学学报
2011年 第5期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
关于我们 | 版权声明 | 联系我们 | 帮助中心| 意见反馈
主办单位：上海市教育委员会
技术支持：重庆维普资讯有限公司
版权所有© 2001-2026 渝B2-20050021-1渝公网安备 50019002500403号
使用帮助 返回顶部