Article

National institute of informatics, japan at TRECVID 2007: BBC rushes summarization

Authors:

Duy-Dinh Le,

Shin'ichi SatohAuthors Info & Claims

TVS '07: Proceedings of the international workshop on TRECVID video summarization

Pages 70 - 73

https://doi.org/10.1145/1290031.1290044

Published: 28 September 2007 Publication History

Get Access

Abstract

In this paper, we present a method for BBC rushes summarization. In the proposed method, first the input video is decomposed into fragments by comparing consecutive frames. Next, these fragments are grouped by a clustering method. Using the clustering result, consecutive fragments are grouped into segments. Then the adjacent segments are merged if the distance between them falls below a threshold. Finally, to generate the summaries, we select a subset of the frames of the longest segment in each cluster. The performance of the proposed method on TRECVID 2007 test set is reported.

References

[1]

M. Flickner, H. S. Sawhney, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic, D. Steele, and P. Yanker. Query by image and video content: The qbic system. IEEE Computer, 28(9):23--32, 1995.

Digital Library

Google Scholar

[2]

M. E. Houle. Clustering without data: the GreedyRSC heuristic. In Proc. Intl. Workshop on Data-Mining and Statistical Science (DMSS), pages 62--69, 2006.

Google Scholar

[3]

M. E. Houle. Clustering without data: the Relevant Set Correlation model. In Proc. Intl. Workshop on Data-Mining and Statistical Science (DMSS), pages 54--61, 2006.

Google Scholar

[4]

D.-D. Le, S. Satoh, and M. E. Houle. Boosting face retrieval by using relevant set correlation clustering. In Proc. Int. Conf. on Multimedia and Expo, 2007. Figure 9: Performance on RE measure (Was there a lot of duplicate video:1 strongly agree - 5 strongly disagree).

Crossref

Google Scholar

[5]

P. Over, T. Ianeva, W. Kraaij, and A. F. Smeaton. TRECVID 2006 - An overview. In Proceedings of TRECVID 2006. NIST, USA, 2006.

Google Scholar

[6]

P. Over, A. F. Smeaton, and P. Kelly. The TRECVID 2007 BBC rushes summarization evaluation pilot. In Proceedings of the TRECVID Workshop on Video Summarization (TVS'07), pages 1--15. ACM Press, September 2007.

Digital Library

Google Scholar

[7]

M. A. Stricker and M. Orengo. Similarity of color images. In Proc. of SPIE, Storage and Retrieval for Image and Video Databases III, volume 2420, pages 381--392, Mar 1995.

Crossref

Google Scholar

Cited By

View all

Nguyen DTran MNguyen V(2015)Comics Instance Search with Bag of Visual WordsProceedings of the Second International Conference on Future Data and Security Engineering - Volume 944610.1007/978-3-319-26135-5_22(299-313)Online publication date: 23-Nov-2015
https://dl.acm.org/doi/10.1007/978-3-319-26135-5_22
Iparraguirre JDelrieux C(2014)Online Video Summarization Based on Local FeaturesInternational Journal of Multimedia Data Engineering and Management10.4018/ijmdem.20140401035:2(41-53)Online publication date: 1-Apr-2014
https://doi.org/10.4018/ijmdem.2014040103
Almeida JLeite NTorres R(2013)Online video summarization on compressed domainJournal of Visual Communication and Image Representation10.1016/j.jvcir.2012.01.00924:6(729-738)Online publication date: Aug-2013
https://doi.org/10.1016/j.jvcir.2012.01.009
Show More Cited By

Index Terms

National institute of informatics, japan at TRECVID 2007: BBC rushes summarization
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Unsupervised learning
        Cluster analysis
2. Information systems
  1. Information retrieval
    1. Document representation
    2. Search engine architectures and scalability
      1. Search engine indexing

Recommendations

NTU TRECVID-2007 fast rushes summarization system
TVS '07: Proceedings of the international workshop on TRECVID video summarization

Rushes are the raw materials used to produce a video. They often contain redundant and repetitive contents. Rushes summarization aims to provide a quick overview for a rushes video. As part of TRECVID 2007, NIST initiates a rushes summarization task. ...
Rushes summarization using different redundancy elimination approaches
TVS '08: Proceedings of the 2nd ACM TRECVid Video Summarization Workshop

Generating short summary videos for rushes is a challenging task due to the difficulty in eliminating redundancy and determining the important objects and events to be placed in the summary. Redundancy elimination is difficult since repetitive segments, ...
THU-intel at rushes summarization of TRECVID 2008
TVS '08: Proceedings of the 2nd ACM TRECVid Video Summarization Workshop

Video summary is an active research field to help users to grasp a whole video's content for efficient browsing and editing. In this paper, we describe our THU-Intel rushes summarization system in TRECVID2008. In our approach, we first extract low-level ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

TVS '07: Proceedings of the international workshop on TRECVID video summarization

September 2007

108 pages

ISBN:9781595937803

DOI:10.1145/1290031

General Chairs:
Paul Over
NIST, USA
,
Alan F. Smeaton
Dublin City University, Ireland

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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 September 2007

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

MM07

Sponsor:

MM07: The 15th ACM International Conference on Multimedia 2007

September 28, 2007

Bavaria, Augsburg, Germany

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

9
Total Citations
View Citations
197
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 12 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Nguyen DTran MNguyen V(2015)Comics Instance Search with Bag of Visual WordsProceedings of the Second International Conference on Future Data and Security Engineering - Volume 944610.1007/978-3-319-26135-5_22(299-313)Online publication date: 23-Nov-2015
https://dl.acm.org/doi/10.1007/978-3-319-26135-5_22
Iparraguirre JDelrieux C(2014)Online Video Summarization Based on Local FeaturesInternational Journal of Multimedia Data Engineering and Management10.4018/ijmdem.20140401035:2(41-53)Online publication date: 1-Apr-2014
https://doi.org/10.4018/ijmdem.2014040103
Almeida JLeite NTorres R(2013)Online video summarization on compressed domainJournal of Visual Communication and Image Representation10.1016/j.jvcir.2012.01.00924:6(729-738)Online publication date: Aug-2013
https://doi.org/10.1016/j.jvcir.2012.01.009
Cunha Tde Souza Fde A. Araújo APappa GOssowski SLecca P(2012)Rushes video summarization based on spatio-temporal featuresProceedings of the 27th Annual ACM Symposium on Applied Computing10.1145/2245276.2245287(45-50)Online publication date: 26-Mar-2012
https://dl.acm.org/doi/10.1145/2245276.2245287
Peng YYao JWang JBoujemaa NRamirez NNatsev A(2010)AdaOUBoostProceedings of the international conference on Multimedia information retrieval10.1145/1743384.1743408(111-118)Online publication date: 29-Mar-2010
https://dl.acm.org/doi/10.1145/1743384.1743408
Liu YLiu YChan K(2009)Dimensionality reduction for heterogeneous dataset in rushes editingPattern Recognition10.1016/j.patcog.2008.06.01642:2(229-242)Online publication date: 1-Feb-2009
https://dl.acm.org/doi/10.1016/j.patcog.2008.06.016
Noguchi AYanai KOver PSmeaton A(2008)Rushes summarization based on color, motion and faceProceedings of the 2nd ACM TRECVid Video Summarization Workshop10.1145/1463563.1463589(139-143)Online publication date: 31-Oct-2008
https://dl.acm.org/doi/10.1145/1463563.1463589
Putpuek NLe DCooharojananone NSatoh SLursinsap COver PSmeaton A(2008)Rushes summarization using different redundancy elimination approachesProceedings of the 2nd ACM TRECVid Video Summarization Workshop10.1145/1463563.1463581(100-104)Online publication date: 31-Oct-2008
https://dl.acm.org/doi/10.1145/1463563.1463581
Dumont EMérialdo BOver PSmeaton A(2008)Sequence alignment for redundancy removal in video rushes summarizationProceedings of the 2nd ACM TRECVid Video Summarization Workshop10.1145/1463563.1463572(55-59)Online publication date: 31-Oct-2008
https://dl.acm.org/doi/10.1145/1463563.1463572

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

NTU TRECVID-2007 fast rushes summarization system

Rushes summarization using different redundancy elimination approaches

THU-intel at rushes summarization of TRECVID 2008