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Reseach Article

A Survey on Video Content Identification Tool

by Juhi S. Patil, Rachana A. Satao
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 19
Year of Publication: 2014
Authors: Juhi S. Patil, Rachana A. Satao
10.5120/15097-3451

Juhi S. Patil, Rachana A. Satao . A Survey on Video Content Identification Tool. International Journal of Computer Applications. 85, 19 ( January 2014), 28-31. DOI=10.5120/15097-3451

@article{ 10.5120/15097-3451,
author = { Juhi S. Patil, Rachana A. Satao },
title = { A Survey on Video Content Identification Tool },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 19 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 28-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number19/15097-3451/ },
doi = { 10.5120/15097-3451 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:02:54.963807+05:30
%A Juhi S. Patil
%A Rachana A. Satao
%T A Survey on Video Content Identification Tool
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 19
%P 28-31
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Now-a-days, the search engines available are text-based search engines. Thus using text-based search engines one can efficiently search for the desired video. Many times it happens like video name that has fired as a query, contains irrelevant data. Even recently it is found that some illegal information is communicated via video by embedding it into a longer video. And also it is found that broadcast channels and IPTV services many times use same digital videos. An efficient method of consuming, storing and retrieving such vast amounts of videos is essential. This has led to the emergence of video copy detection as an active area of research. In this survey, a study of different MPEG standard, challenges in video copy detection, brief idea about video fingerprint and its application are discussed.

References
  1. Content Based Video Copy Detection: Issues and Practices, Sanjoy Kumar Saha CSE Department, Jadavpur University Kolkata, India
  2. International Organization for Standardization Organization Internationale De Normalisation Iso/Iec Jtc1/Sc29/Wg11 Coding Of Moving Pictures And Audio.
  3. J. Law-To, , L. Chen, A. Joly, I. Laptev, O. Buisson, V. Gouet-Brunet, N. Boujemaa, and F. Stentiford. Video copy detection: A comparative study. In Proc. CIVR, 2007.
  4. A. Hampapur and R. Bolle. Comparison of sequence matching techniques for video copy detection. In Proc. Intl. Conf. on Multimedia and Expo, pages 188 – 192, 2001.
  5. S. Lee and C. D. Yoo. Video fingerprinting based on centroids of gradient orientations. In Proc. ICASSP, pages 401 – 404, 2006.
  6. S-C. S. Cheung and A. Zakhor. Efficient video similarity measurement with video signature. IEEE Trans. CSVT, 13 No. 1:59–74, 2003.
  7. A. M. Ferman, A. M. Tekalp, and R. Mehrotra. Robust color histogram descriptors for video segment retrieval and identification. IEEE Trans. on IP, 11(5):497 – 508, 2002.
  8. Y. Li, J. S. Jin, and X. Zhou. Video matching using binary signature. In Proc. Intl. Symp. on Intelligent Signal Processing and Comm. Systems, pages 317 – 320, 2005.
  9. R. Radhakrishnan and C. Bauer. Robust video fingerprints based on subspace embed-ding. In Proc. ICASSP, pages 2245–2248, 2008.
  10. A. Hampapur and R. Bolle. Comparison of sequence matching techniques for video copy detection. In Proc. Intl. Conf. on Multimedia and Expo, pages 188 – 192, 2001.
  11. S. Lee and C. D. Yoo. Video fingerprinting based on centroids of gradient orientations. In Proc. ICASSP, pages 401 – 404, 2006.
  12. L. Chen and T. S. Chua. A match and tiling approach to content-based video retrieval. In Proc. Intl. Conf. on Multimedia and Expo, 2001.
  13. M. C. Yeh and K. -Y. Cheng. A compact, effective descriptor for video copy detection. In Proc. of ACM Multimedia, 2009.
  14. R. Mohan. Video sequence matching. In Proc. ICASSP, pages 3697 – 3700, 1998.
  15. C. Kim and B. Vasudev. Spatiotemporal sequence matching for efficient video copy detection. IEEE Trans. on CSVT, 15, No. 1:127 – 132, 2005.
  16. L. Chen and F. W. M. Stentiford. Video sequence matching based on temporal ordinal measurement. Pattern Recognition Letters, 29:1824–1831, 2008.
  17. R. C. Harvey and M. Heefeda. Spatio-temporal video copy detection. In Proc. Multi-media System conference, pages 35 – 46, 2012.
  18. A. K. Jain, A. Vailaya, and W. Xiong. Query by clip. Multimedia System Journal, 7,No. 5:369 – 384, 1999.
  19. S-C. S. Cheung and A. Zakhor. Efficient video similarity measurement with video signature. IEEE Trans. CSVT, 13 No. 1:59–74, 2003.
  20. K. W. Sze, K. M. Lam, and G. Qiu. A new key frame representation for video segment retrieval. IEEE Trans. CSVT, 15 No. 9:1148 – 1155, 2005.
  21. A. Hampapur, K. Hyun, and R. Bolle, Comparison of sequence matching techniques for video copy detection, nProc. Conf. Storage Retrieval Media Databases, 2002, pp. 194–201.
Index Terms

Computer Science
Information Sciences

Keywords

Video copy detection video fingerprint MPEG standards