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Rushes summarization based on color, motion and face

Authors:

Akitsugu Noguchi,

Keiji YanaiAuthors Info & Claims

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

Pages 139 - 143

https://doi.org/10.1145/1463563.1463589

Published: 31 October 2008 Publication History

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Abstract

In this paper, we present a method for the Rushes Summarization task which is one of tasks of TRECVID 2008. In the proposed method, first an input video is decomposed into shots by comparing consecutive frames. Then, these shots are grouped by the k-means method, using color, motion and faces as features. In the preliminary experiments, we compared three systems which employed the following feature combinations: "color", "color and motion" and "color, motion and faces". As a result, we found out that motion features and face features were effective.

Our results of Rushes Summarization 2008 were a little below the median regarding IN (inclusion ratio of ground truth) and JU (lack of junk shots), but were above the median regarding TE (pleasant tempo). Then, to improve IN and JU, we modified the method to detect clapper boards by introducing visual feature in addition to sound feature. The additional experiment regarding the modification after submission shows that it improved the results.

References

[1]

G. Csurka, C. Bray, C. Dance, and L. Fan. Visual categorization with bags of keypoints. In Proc. of ECCV Workshop on Statistical Learning in Computer Vision, pages 1--22, 2004.

Google Scholar

[2]

A. Hauptmann, M. Christel, W. Lin, B. Maher, J. Yang, R. Baron, and G. Xiang. Clever clustering vs. simple speed-up for summarizing rushes. In Proc. of the International Workshop on TRECVID Video Summarization, pages 20--24, 2007.

Digital Library

Google Scholar

[3]

D. Le and S. Satoh. National institute of informatics, japan at trecvid 2007: BBC rushes summarization. In Proc. of the International Workshop on TRECVID Video Summarization, pages 70--73, 2007.

Digital Library

Google Scholar

[4]

Y. Liu, Y. Liu, and Y. Zhang. The hong kong polytechnic university at trecvid 2007 bbc rushes summarization. In Proc. of the International Workshop on TRECVID Video Summarization, pages 50--54, 2007.

Digital Library

Google Scholar

[5]

D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91--110, 2004.

Digital Library

Google Scholar

[6]

B. Lucas and T. Kanade. An iterative image registration technique with an application to stereo vision. In Proc. of International Joint Conference on Artificial Intelligence, pages 674--679, 1981.

Digital Library

Google Scholar

[7]

P. Over, A. F. Smeaton, and G. Awad. The TRECVID 2008 BBC rushes summarization evaluation. In Proc. of the International Workshop on TRECVID Video Summarization, pages 1--20, New York, NY, USA, 2008. ACM.

Digital Library

Google Scholar

[8]

P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. In Proc. IEEE Computer Vision and Pattern Recognition, volume 1, pages 511--518, 2001.

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Cooharojananone NPutpuek NSatoh SLursinsap C(2009)A Novel Retake Detection Using LCS and SIFT AlgorithmProceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing10.1007/978-3-642-10467-1_68(777-787)Online publication date: 15-Dec-2009
https://dl.acm.org/doi/10.1007/978-3-642-10467-1_68
Over PSmeaton AAwad GOver PSmeaton A(2008)The trecvid 2008 BBC rushes summarization evaluationProceedings of the 2nd ACM TRECVid Video Summarization Workshop10.1145/1463563.1463564(1-20)Online publication date: 31-Oct-2008
https://dl.acm.org/doi/10.1145/1463563.1463564

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Rushes summarization based on color, motion and face

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This paper proposes a new framework to formulate summarization of rushes video as an unsupervised learning problem. We pose the problem of video summarization as one of time-series clustering, and proposed Constrained Aligned Cluster Analysis (CACA). ...

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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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Association for Computing Machinery

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Published: 31 October 2008

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October 31, 2008

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Cooharojananone NPutpuek NSatoh SLursinsap C(2009)A Novel Retake Detection Using LCS and SIFT AlgorithmProceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing10.1007/978-3-642-10467-1_68(777-787)Online publication date: 15-Dec-2009
https://dl.acm.org/doi/10.1007/978-3-642-10467-1_68
Over PSmeaton AAwad GOver PSmeaton A(2008)The trecvid 2008 BBC rushes summarization evaluationProceedings of the 2nd ACM TRECVid Video Summarization Workshop10.1145/1463563.1463564(1-20)Online publication date: 31-Oct-2008
https://dl.acm.org/doi/10.1145/1463563.1463564

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NTU TRECVID-2007 fast rushes summarization system

Rushes video summarization using audio-visual information and sequence alignment

Unsupervised summarization of rushes videos

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