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Rushes summarization based on color, motion and face
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Source
International Multimedia Conference archive
Proceedings of the 2nd ACM TRECVid Video Summarization Workshop table of contents
Vancouver, British Columbia, Canada
Pages 139-143  
Year of Publication: 2008
ISBN:978-1-60558-309-9
Authors
Akitsugu Noguchi  The University of Electro-Communications, Tokyo, Japan
Keiji Yanai  The University of Electro-Communications, Tokyo, Japan
Sponsors
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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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

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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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.


Collaborative Colleagues:
Akitsugu Noguchi: colleagues
Keiji Yanai: colleagues