research-article

Binary tree based on-line video summarization

Authors:

Víctor Valdés,

José M. MartínezAuthors Info & Claims

TVS '08: Proceedings of the 2nd ACM TRECVid Video Summarization Workshop

Pages 134 - 138

https://doi.org/10.1145/1463563.1463588

Published: 31 October 2008 Publication History

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Abstract

This paper describes our method for the TRECVID 2008 BBC rushes summarization task, a fully on-line video abstraction algorithm with customizable memory and computation requirements which enables the application of different abstraction criteria. The algorithm is based on the dynamic generation of binary trees which model the different choices for abstract output. In this work the generic abstraction algorithm as well as the specific abstraction criteria applied for the BBC rushes summarization task are presented together with an overview of the algorithm capabilities.

References

[1]

Valdés, V., Martínez J.M. On-line Video Skimming Based on Histogram similarity. Proc. of ACM Multimedia 2007 (TVS Workshop), pp. 94--98.

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Google Scholar

[2]

Valdés, V., Martínez J.M. Post-processing Techniques for On-line Adaptive Video Summarization Based on Relevance Curves. Semantic Media and Digital Media Technologies - SAMT07, LNCS, Vol. 4816, Springer Verlag, 2007, pp. 144--157.

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Google Scholar

[3]

Valdés, V., Martínez J.M. On-Line Video Summarization Based on Signature-Based Junk and Redundancy Filtering. Proc. WIAMIS08, pp. 88--19.

Digital Library

Google Scholar

[4]

Over, P. Smeaton, A. F, Kelly, P. The TRECVID 2007 BBC Rushes Summarization Evaluation Pilot. Proc. of ACM Multimedia 2007 (TVS Workshop), pp. 1--15.

Digital Library

Google Scholar

[5]

Kasatuni, E., Yamada A. The MPEG-7 Color Layout Descriptor: a Compact Image Feature for High-Speed Image/Video Segment Retrieval. Proc. of ICIP2001, Vol. 1, pp. 674--677.

Google Scholar

[6]

Hauptmann, A., Ziang, G., Baron, R., Yang, J., Maher, B., Lin, W-H., Christel, M. Clever Clustering vs. Simple Speed-Up for Summarizing Rushes. Proc. of ACM Multimedia 2007 (TVS Workshop), pp. 20--24.

Digital Library

Google Scholar

[7]

Fayzullim M., Subrahmanian V. S., Picariello A., Sapino M. L. The CPR Model for Summarizing Video. Proc. of the 1st ACM Int. Workshop on Multimedia Databases, pp. 2--9, 2003.

Digital Library

Google Scholar

[8]

Lienhart, R., Maydt J. An Extended Set of Haar-like Features for Rapid Object Detection. Proc. of ICIP 2002, Vol.1, pp. 900--903.

Google Scholar

[9]

Over P., Smeaton A. F., Awad G. The TRECVID 2008 BBC Rushes Summarization Evaluation. Proc. of ACM Multimedia 2008 (TVS Workshop), pp. 1--20.

Digital Library

Google Scholar

Cited By

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Gupta DSharma A(2023)A comprehensive study of automatic video summarization techniquesArtificial Intelligence Review10.1007/s10462-023-10429-z56:10(11473-11633)Online publication date: 13-Mar-2023
https://doi.org/10.1007/s10462-023-10429-z
Almeida MVieira CMelo PAssunção R(2019)Random Playlists Smoothly Commuting Between StylesACM Transactions on Multimedia Computing, Communications, and Applications10.1145/336174215:4(1-20)Online publication date: 16-Dec-2019
https://dl.acm.org/doi/10.1145/3361742
Liu ZZhou WLi H(2019)AB-LSTMACM Transactions on Multimedia Computing, Communications, and Applications10.1145/335672815:4(1-23)Online publication date: 16-Dec-2019
https://dl.acm.org/doi/10.1145/3356728
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Index Terms

Binary tree based on-line video summarization
1. Information systems
  1. Information retrieval
    1. Document representation
2. Theory of computation
  1. Semantics and reasoning
    1. Program reasoning
      1. Abstraction

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TVS '08: Proceedings of the 2nd ACM TRECVid Video Summarization Workshop

October 2008

156 pages

ISBN:9781605583099

DOI:10.1145/1463563

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]

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Published: 31 October 2008

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October 31, 2008

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Gupta DSharma A(2023)A comprehensive study of automatic video summarization techniquesArtificial Intelligence Review10.1007/s10462-023-10429-z56:10(11473-11633)Online publication date: 13-Mar-2023
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Almeida MVieira CMelo PAssunção R(2019)Random Playlists Smoothly Commuting Between StylesACM Transactions on Multimedia Computing, Communications, and Applications10.1145/336174215:4(1-20)Online publication date: 16-Dec-2019
https://dl.acm.org/doi/10.1145/3361742
Liu ZZhou WLi H(2019)AB-LSTMACM Transactions on Multimedia Computing, Communications, and Applications10.1145/335672815:4(1-23)Online publication date: 16-Dec-2019
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Ye ZPeng Y(2019)Sequential Cross-Modal Hashing Learning via Multi-scale Correlation MiningACM Transactions on Multimedia Computing, Communications, and Applications10.1145/335633815:4(1-20)Online publication date: 26-Dec-2019
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Liu SHuang Z(2019)Efficient Image Hashing with Geometric Invariant Vector Distance for Copy DetectionACM Transactions on Multimedia Computing, Communications, and Applications10.1145/335539415:4(1-22)Online publication date: 16-Dec-2019
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K. VSen DRaman B(2019)Video SkimmingACM Computing Surveys10.1145/334771252:5(1-38)Online publication date: 13-Sep-2019
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Paul MMusfequs Salehin M(2019)Spatial and Motion Saliency Prediction Method Using Eye Tracker Data for Video SummarizationIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2018.284478029:6(1856-1867)Online publication date: Jun-2019
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Kumar KShrimankar D(2018)Deep Event Learning boosT-up ApproachMultimedia Tools and Applications10.1007/s11042-018-5882-z77:20(26635-26655)Online publication date: 1-Oct-2018
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The Hong Kong Polytechnic University at TRECVID 2007 BBC rushes summarization

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