skip to main content
10.1145/1291233.1291294acmconferencesArticle/Chapter ViewAbstractPublication PagesmmConference Proceedingsconference-collections
Article

Mining repetitive clips through finding continuous paths

Published: 29 September 2007 Publication History

Abstract

Automatically discovering repetitive clips from large video database is a challenging problem due to the enormous computational cost involved in exploring the huge solution space. Without any a priori knowledge of the contents, lengths and total number of the repetitive clips, we need to discover all of them in the video database. To address the large computational cost, we propose a novel method which translates repetitive clip mining to the continuous path finding problem in a matching trellis, where sequence matching can be accelerated by taking advantage of the temporal redundancies in the videos. By applying the locality sensitive hashing (LSH) for efficient similarity query and the proposed continuous path finding algorithm, our method is of only quadratic complexity of the database size. Experiments conducted on a 10.5-hour TRECVID news dataset have shown the effectiveness, which can discover repetitive clips of various lengths and contents in only 25 minutes, with features extracted off-line.

References

[1]
M. Datar, N. Immorlica, P. Indyk, and V. Mirrokni. Locality-sensitive hashing scheme based on p-stable distribution. In Proc. DIMACS workshop on Streaming Data Analysis and Mining, 2003.
[2]
C. Herley. Argos: Automatically extracting repeating objects from multimedia streams. IEEE Trans. on Multimedia, 8(1):115--129, 2006.
[3]
K. Kashino, T. Kurozumi, and H. Murase. A quick search method for audio and video signals based on histogram pruning. IEEE Trans. on Multimedia, 2003.
[4]
K. M. Pua, J. M. Gauch, S. E. Gauch, and J. Z. Miadowicz. Realtime repeated video sequence identification. Computer Vision and Image Understanding, 2004.
[5]
R. Lienhart, C. Kuhmuench, and W. Effelsberg. On the detection and recognition of television commercials. In Proc. IEEE Conf. on Multimedia Computing and Systems, 1997.
[6]
S. Satoh. News video analysis based on identical shot detection. In Proc. IEEE Conf. on Multimedia Expo, 2002.
[7]
P. Wang, Z.-Q. Liu, and S.-Q. Yang. A probabilistic template-based approach to discovering repetitive patterns in broadcast videos. In Proc. ACM Multimedia, 2005.
[8]
L. Xie, L. Kennedy, S.-F. Chang, A. Divakaran, H. Sun, and C.-Y. Lin. Discovering meaningful multimedia patterns with audio-visual concepts and associated text. In Proc. IEEE Conf. on Image Processing, 2004.
[9]
X. Yang, P. Xue, and Q. Tian. A repeated video clip identification system. In Proc. ACM Multimedia, 2005.
[10]
J. Yuan, L.-Y. Duan, Q. Tian, and C. Xu. Fast and robust short video clip search using an index structure. In Proc. ACM Multimedia Workshop on Multimedia Information Retrieval, 2004.
[11]
D.-Q. Zhang and S.-F. Chang. Detecting image near-duplicate by stochastic attributed relational graph matching with learning. In Proc. ACM Multimedia, 2004.

Cited By

View all
  • (2011)TV program segmentation using multi-modal information fusionProceedings of the 1st ACM International Conference on Multimedia Retrieval10.1145/1991996.1992007(1-8)Online publication date: 18-Apr-2011
  • (2010)A fast video copy detection approach by dynamic programmingProceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I10.5555/1884564.1884616(558-567)Online publication date: 21-Sep-2010
  • (2010)Recovering the Topology of Multiple Cameras by Finding Continuous Paths in a TrellisProceedings of the 2010 20th International Conference on Pattern Recognition10.1109/ICPR.2010.864(3541-3544)Online publication date: 23-Aug-2010
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
MM '07: Proceedings of the 15th ACM international conference on Multimedia
September 2007
1115 pages
ISBN:9781595937025
DOI:10.1145/1291233
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 September 2007

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. repetitive pattern discovery
  2. video data mining

Qualifiers

  • Article

Conference

MM07

Acceptance Rates

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 20 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2011)TV program segmentation using multi-modal information fusionProceedings of the 1st ACM International Conference on Multimedia Retrieval10.1145/1991996.1992007(1-8)Online publication date: 18-Apr-2011
  • (2010)A fast video copy detection approach by dynamic programmingProceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I10.5555/1884564.1884616(558-567)Online publication date: 21-Sep-2010
  • (2010)Recovering the Topology of Multiple Cameras by Finding Continuous Paths in a TrellisProceedings of the 2010 20th International Conference on Pattern Recognition10.1109/ICPR.2010.864(3541-3544)Online publication date: 23-Aug-2010
  • (2010)A Fast Video Copy Detection Approach by Dynamic ProgrammingAdvances in Multimedia Information Processing - PCM 201010.1007/978-3-642-15702-8_51(558-567)Online publication date: 2010
  • (2010)Mining TV Broadcasts 24/7 for Recurring Video SequencesVideo Search and Mining10.1007/978-3-642-12900-1_13(327-356)Online publication date: 2010
  • (2009)Mining Repetitive Patterns in Multimedia DataEncyclopedia of Data Warehousing and Mining, Second Edition10.4018/978-1-60566-010-3.ch200(1287-1291)Online publication date: 2009
  • (2009)Mining TV broadcasts for recurring video sequencesProceedings of the ACM International Conference on Image and Video Retrieval10.1145/1646396.1646432(1-8)Online publication date: 8-Jul-2009
  • (2009)Video frame-matching algorithm using dynamic programmingJournal of Electronic Imaging10.1117/1.309236718:1(010504)Online publication date: 1-Jan-2009
  • (2008)Mining Recurring Events Through Forest GrowingIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2008.200561618:11(1597-1607)Online publication date: Nov-2008

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media