Article

Video rushes summarization by adaptive acceleration and stacking of shots

Authors:

Marcin Detyniecki,

Christophe MarsalaAuthors Info & Claims

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

Pages 65 - 69

https://doi.org/10.1145/1290031.1290043

Published: 28 September 2007 Publication History

Get Access

Abstract

When witnessing the great increase of video data available, it becomes clear that summarization is one of the great challenges ahead. One particular problem is the summarization of video rushes.

In this paper we present a straightforward approach that addresses this specific challenge. It combines two complementary actions: shot selection by stacking and adaptive acceleration of the playback.

This simple approach provides excellent results, compared at TRECVid 2007. In particular, it offers easy to understand summaries that keep most of the original information, that meet the target compression rate, that have average scores of redundancy perception and that show playing times (by the judges) almost equal to the summaries duration.

References

[1]

T. Bärecke, E. Kijak, A. Nürnberger, and M. Detyniecki. Summarizing video information using self-organizing maps. In Proceedings of the IEEE International Conference on Fuzzy Systems - FUZZ--IEEE, pages 540--546, Vancouver, Canada, July 2006.

Crossref

Google Scholar

[2]

N. Boujemaa, J. Fauqueur, and V. Gouet. What's beyond query by example? In L. Shapiro, H. Kriegel, and R. Veltkamp, editors, Trends and Advances in Content-Based Image and Video Retrieval, LNCS. Springer Verlag, 2004.

Google Scholar

[3]

Y. Li, S.-H. Lee, C.-H. Yeh, and C.-C. J. Kuo. Techniques for movie content analysis and skimming: tutorial and overview on video abstraction techniques. IEEE Signal Processing Magazine, pages 79--89, 2006.

Google Scholar

[4]

C.-Y. Lin and E. Hovy. From single to multi-document summarization: A prototype system and its evaluation. In Proceedings of the ACL, pages 457--464, 2002.

Digital Library

Google Scholar

[5]

I. Mani. Automatic Summarization. John Benjamins Pub Co, 2001. ISBN: 978-1588110602.

Google Scholar

[6]

K. McKeown, R. J. Passonneau, D. K. Elson, A. Nenkova, and J. Hirschberg. Do summaries help? a task-based evaluation of multi-document summarization. In Proceedings of SIGIR05, Salvador, Brazil 2005.

Digital Library

Google Scholar

[7]

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

Digital Library

Google Scholar

[8]

K. Peker and A. Divakaran. Adaptive fast playback based video skimming using a compressed-domain visual complexity measure. In IEEE International Conference on Multimedia and Expo 2004 (ICME'04), volume 3, pages 2055--2058, 2004.

Crossref

Google Scholar

[9]

K. A. Peker, A. Divakaran, and S. Huifang. Constant pace skimming and temporal sub-sampling of video using motion activity. In Proc. of the International Conference on Image Processing, volume 3, pages 414--417, Thessaloniki, Greece, October 2001.

Crossref

Google Scholar

[10]

F. Shipman, A. Girgensohn, and L. Wilcox. Generation of interactive multi-level video summaries. In Proc. of the eleventh ACM international conference on Multimedia, pages 392--401, Berkeley, Ca. (USA), 2003.

Digital Library

Google Scholar

[11]

A. F. Smeaton, P. Over, and W. Kraaij. Evaluation campaigns and TRECVid. In MIR '06: Proceedings of the 8th ACM International Workshop on Multimedia Information Retrieval, pages 321--330, New York, NY, USA, 2006. ACM Press.

Digital Library

Google Scholar

[12]

A. Tombros and M. Sanderson. Advantages of query biased summaries in information retrieval. In Research and Development in Information Retrieval, pages 2--10, 1998.

Digital Library

Google Scholar

[13]

Z. Xiong, R. Radhakrishnan, A. Divakaran, Y. Rui, and T. Hang. A Unified Framework for Video Summarization, Browsing and Retrieval: With Applications to Consumer And Surveillance Video. Academic Press, 2006.

Digital Library

Google Scholar

Cited By

View all

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
Li LZhou KXue GZha HYu YSadagopan SRamamritham KKumar ARavindra MBertino EKumar R(2011)Video summarization via transferrable structured learningProceedings of the 20th international conference on World wide web10.1145/1963405.1963448(287-296)Online publication date: 28-Mar-2011
https://dl.acm.org/doi/10.1145/1963405.1963448
Money AAgius H(2010)ELVISACM Transactions on Multimedia Computing, Communications, and Applications10.1145/1823746.18237516:3(1-30)Online publication date: 27-Aug-2010
https://dl.acm.org/doi/10.1145/1823746.1823751
Show More Cited By

Index Terms

Video rushes summarization by adaptive acceleration and stacking of shots
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
2. Information systems
  1. Information systems applications
    1. Multimedia information systems

Recommendations

Adaptive acceleration and shot stacking for video rushes summarization
TVS '08: Proceedings of the 2nd ACM TRECVid Video Summarization Workshop

As the amount of recorded video data continually increases, a lot of teams around the world work to propose original methods on automatic video summarization. A particular kind of video is a rush: a rough draft of a movie or a documentary. In this paper,...
Rushes video summarization using audio-visual information and sequence alignment
TVS '08: Proceedings of the 2nd ACM TRECVid Video Summarization Workshop

This paper describes our system and methodologies for the BBC rushes video summarization task of TRECVID 2008. The procedure of the system is composed of three major steps: shot detection, irrelevant and repetitive subshot removal, and final summary ...
Automatic summarization of rushes video using bipartite graphs

In this paper we present a new approach for automatic summarization of rushes, or unstructured video. Our approach is composed of three major steps. First, based on shot and sub-shot segmentations, we filter sub-shots with low information content not ...

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

10
Total Citations
View Citations
247
Total Downloads

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

Reflects downloads up to 12 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

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
Li LZhou KXue GZha HYu YSadagopan SRamamritham KKumar ARavindra MBertino EKumar R(2011)Video summarization via transferrable structured learningProceedings of the 20th international conference on World wide web10.1145/1963405.1963448(287-296)Online publication date: 28-Mar-2011
https://dl.acm.org/doi/10.1145/1963405.1963448
Money AAgius H(2010)ELVISACM Transactions on Multimedia Computing, Communications, and Applications10.1145/1823746.18237516:3(1-30)Online publication date: 27-Aug-2010
https://dl.acm.org/doi/10.1145/1823746.1823751
Kim HKim Y(2010)Toward a conceptual framework of key‐frame extraction and storyboard display for video summarizationJournal of the American Society for Information Science and Technology10.1002/asi.2131761:5(927-939)Online publication date: Mar-2010
https://doi.org/10.1002/asi.21317
Hidaka KSatou T(2009)The Journal of The Institute of Image Information and Television Engineers10.3169/itej.63.3663:1(36-41)Online publication date: 2009
https://doi.org/10.3169/itej.63.36
Rossi EBenini SLeonardi RMansencal BBenois-Pineau J(2009)Clustering of scene repeats for essential rushes preview2009 10th Workshop on Image Analysis for Multimedia Interactive Services10.1109/WIAMIS.2009.5031476(234-237)Online publication date: May-2009
https://doi.org/10.1109/WIAMIS.2009.5031476
Chen BWang JWang J(2009)A novel video summarization based on mining the story-structure and semantic relations among concept entitiesIEEE Transactions on Multimedia10.1109/TMM.2008.200970311:2(295-312)Online publication date: 1-Feb-2009
https://dl.acm.org/doi/10.1109/TMM.2008.2009703
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
Detyniecki MMarsala COver PSmeaton A(2008)Adaptive acceleration and shot stacking for video rushes summarizationProceedings of the 2nd ACM TRECVid Video Summarization Workshop10.1145/1463563.1463583(109-113)Online publication date: 31-Oct-2008
https://dl.acm.org/doi/10.1145/1463563.1463583
Chen FAdcock JCooper MOver PSmeaton A(2008)A simplified approach to rushes summarizationProceedings of the 2nd ACM TRECVid Video Summarization Workshop10.1145/1463563.1463573(60-64)Online publication date: 31-Oct-2008
https://dl.acm.org/doi/10.1145/1463563.1463573

View Options

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

Adaptive acceleration and shot stacking for video rushes summarization

Rushes video summarization using audio-visual information and sequence alignment

Automatic summarization of rushes video using bipartite graphs