research-article

TV program segmentation using multi-modal information fusion

Authors:

Yuan DongAuthors Info & Claims

ICMR '11: Proceedings of the 1st ACM International Conference on Multimedia Retrieval

Article No.: 11, Pages 1 - 8

https://doi.org/10.1145/1991996.1992007

Published: 18 April 2011 Publication History

Abstract

A TV program segmentation algorithm is presented by the fusion of the multi-modal information in the large-scale videos. As "Inter-Programs" are generally inserted into the TV videos repeatedly, the macro structures of the videos can be effectively and automatically generated by identifying the video-audio features of the special sequences. The Electronic Program Guide (EPG) is used to organize the structures into the programs. Three sections are included in the algorithm, namely, the video-based non-supervised duplicate sequence detection, the audio-based special clip retrieval and the EPG-based 24-hour program segmentation. The algorithm has been tested in 60-day different-type TV videos. The F-measures of the multi-modal fusion and video-based duplicated sequence detection achieve the rates of over 98% and 96% respectively. These results show that the proposed method is highly efficient and effective for the TV Program segmentation.

References

[1]

H. Bai, C. Dong, L. Wang, G. Qin, K. Tao, X. Chang, and Y. Dong. Non-supervised macro segmentation of large-scale tv videos. In Multimedia Content Access: Algorithms and Systems V, 2011.

[2]

H. Bai, W. Hu, T. Wang, X. Tong, C. Liu, and Y. Zhang. A novel sports video logo detector based on motion analysis. In International Conference of Neural Information Processing, pages 448--457, 2006.

Digital Library

[3]

J. L. Bentley. Multidimensional binary search trees used for associative searching. Commun. ACM, 18(9):509--517, 1975.

Digital Library

[4]

S.-A. Berrani, G. Manson, and P. Lechat. A non-supervised approach for repeated sequence detection in tv broadcast streams. Image Commun., 23(7):525--537, 2008.

Digital Library

[5]

M. Datar, N. Immorlica, P. Indyk, and V. S. Mirrokni. Locality-sensitive hashing scheme based on p-stable distributions. In Annual symposium on Computational geometry, pages 253--262, 2004.

Digital Library

[6]

I. Döhring and R. Lienhart. Fast and effective features for recognizing recurring video clips in very large databases. In International Conference of Image Analysis and Processing, pages 65--70, 2007.

Digital Library

[7]

I. Döhring and R. Lienhart. Mining tv broadcasts for recurring video sequences. In International Conference on Image and Video Retrieval, pages 1--8, 2009.

Digital Library

[8]

A. Ekin and A. M. Tekalp. Automatic soccer video analysis and summarization. IEEE Trans. on Image Processing, 12:796--807, 2003.

Digital Library

[9]

A. Gionis, P. Indyk, and R. Motwani. Similarity search in high dimensions via hashing. In International Conference on Very Large Data Bases, pages 518--529, 1999.

Digital Library

[10]

J. Haitsma, T. Kalker, and J. Oostveen. An efficient database search strategy for audio fingerprinting. In IEEE Workshop on Multimedia Signal Processing, pages 178--181, 2002.

[11]

P. Indyk and R. Motwani. Approximate nearest neighbors: towards removing the curse of dimensionality. In ACM symposium on Theory of computing, pages 604--613, 1998.

Digital Library

[12]

Y. Ke, D. Hoiem, and R. Sukthankar. Computer vision for music identification: Video demonstration. In CVPR, 2005.

Digital Library

[13]

R. Lienhart, C. Kuhmünch, and W. Effelsberg. On the detection and recognition of television commercials. In International Conference on Multimedia Computing and Systems, pages 509--516, 1997.

Digital Library

[14]

G. Manson, X. Naturel, and S.-A. Berrani. Online macro-segmentation of television streams. In International Conference on Advances in Multimedia Modeling, pages 220--221, 2009.

Digital Library

[15]

X. Naturel and P. Gros. A fast shot matching strategy for detecting duplicate sequences in a television stream. In International workshop on Computer vision meets databases, pages 21--27, 2005.

Digital Library

[16]

X. Naturel and P. Gros. Detecting repeats for video structuring. Multimedia Tools Appl., 38(2):233--252, 2008.

Digital Library

[17]

S. B. Needleman and C. D. Wunsch. An efficient method applicable to the search for similarities in the amino acid sequences of two proteins. Journal of Molecular Biology, 48:444--453, 1970.

[18]

L. Rabiner and B. H. Juang. Fundamentals of Speech Recognition. Prentice-Hall, Inc., 1993.

Digital Library

[19]

P. H. Sellers. An algorithm for the distance between two finite sequences. Journal of Combinatorial Theory, A16:253--258, 1974.

[20]

A. Shivadas and J. M. Gauch. Real-time commercial recognition using color moments and hashing. In Canadian Conference on Computer and Robot Vision, pages 465--472, 2007.

Digital Library

[21]

A. F. Smeaton, P. Over, and A. R. Doherty. Video shot boundary detection: Seven years of trecvid activity. Computer Vision and Image Understanding, 114(4):411--418, 2010.

Digital Library

[22]

A. F. Smeaton, P. Over, and W. Kraaij. Evaluation campaigns and trecvid. In International Workshop on Multimedia Information Retrieval, pages 321--330, 2006.

Digital Library

[23]

X. Yang, Q. Tian, and P. Xue. Efficient short video repeat identification with application to news video structure analysis. IEEE Transactions on Multimedia, 9(3):600--609, 2007.

Digital Library

[24]

J. Yuan, W. Wang, J. Meng, Y. Wu, and D. Li. Mining repetitive clips through finding continuous paths. In International conference on Multimedia, pages 289--292, 2007.

Digital Library

Cited By

Dong YWang LLian SCen SLiu W(2015)A novel feature fusion based framework for efficient shot indexing to massive web videosTelecommunications Systems10.1007/s11235-014-9945-959:3(401-413)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.1007/s11235-014-9945-9
Pereira MSouza CPádua FSilva GAssis GPereira A(2015)SAPTEMultimedia Tools and Applications10.1007/s11042-014-2311-974:23(10923-10963)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1007/s11042-014-2311-9
Dong YWang LZhang JBai HZhao J(2013)Macro Segmentation and Content Analysis of TV Broadcast StreamApplied Mechanics and Materials10.4028/www.scientific.net/AMM.284-287.3194284-287(3194-3198)Online publication date: Jan-2013
https://doi.org/10.4028/www.scientific.net/AMM.284-287.3194
Show More Cited By

Index Terms

TV program segmentation using multi-modal information fusion
1. Information systems
  1. Information retrieval

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Information

Published In

cover image ACM Conferences

ICMR '11: Proceedings of the 1st ACM International Conference on Multimedia Retrieval

April 2011

512 pages

ISBN:9781450303361

DOI:10.1145/1991996

General Chairs:
Francesco G. B. De Natale
University of Trento, Italy
,
Alberto Del Bimbo
University of Florence, Italy
,
Program Chairs:
Alan Hanjalic
University of Amsterdam, Netherlands
,
B. S. Manjunath
University of California, Santa Barbara
,
Shin'ichi Satoh
NII, Japan

Copyright © 2011 ACM.

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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SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 April 2011

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ICMR'11

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SIGMM

ICMR'11: International Conference on Multimedia Retrieval

April 18 - 20, 2011

Trento, Italy

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Overall Acceptance Rate 254 of 830 submissions, 31%

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Cited By

Dong YWang LLian SCen SLiu W(2015)A novel feature fusion based framework for efficient shot indexing to massive web videosTelecommunications Systems10.1007/s11235-014-9945-959:3(401-413)Online publication date: 1-Jul-2015
https://dl.acm.org/doi/10.1007/s11235-014-9945-9
Pereira MSouza CPádua FSilva GAssis GPereira A(2015)SAPTEMultimedia Tools and Applications10.1007/s11042-014-2311-974:23(10923-10963)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1007/s11042-014-2311-9
Dong YWang LZhang JBai HZhao J(2013)Macro Segmentation and Content Analysis of TV Broadcast StreamApplied Mechanics and Materials10.4028/www.scientific.net/AMM.284-287.3194284-287(3194-3198)Online publication date: Jan-2013
https://doi.org/10.4028/www.scientific.net/AMM.284-287.3194
Wang LDong YBai HLiu WTao K(2011)A word-based approach for duplicate picture in picture sequence detection2011 4th IEEE International Conference on Broadband Network and Multimedia Technology10.1109/ICBNMT.2011.6155942(286-290)Online publication date: Oct-2011
https://doi.org/10.1109/ICBNMT.2011.6155942

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