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Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval table of contents
Berkeley, California
POSTER SESSION: Posters table of contents
Pages: 262 - 269  
Year of Publication: 2003
ISBN:1-58113-778-8
Authors
Timothy C. Hoad  RMIT University, Melbourne, Australia
Justin Zobel  RMIT University, Melbourne, Australia
Sponsor
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 9,   Downloads (12 Months): 54,   Citation Count: 10
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ABSTRACT

Video data is stored and distributed in large quantities and a wide variety of formats. As the amount of material increases, so too does the need to manage and search it. In previous work, we addressed the problem of rapidly locating a given clip in a large stream of video by analysing the pattern of edits or cuts, a method that is fast and as effective as a standard search method based on image comparison, but is not very robust, particularly for short clips. In this paper we describe two new methods that address the limitations of the cut-based approach. We show that the new video representations are more robust than any previous method and vastly superior at identifying similar content when the cut-based signature is not sufficiently discriminatory.


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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CITED BY  10

Collaborative Colleagues:
Timothy C. Hoad: colleagues
Justin Zobel: colleagues