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Tagboards for video tagging

Published: 26 October 2008 Publication History

Abstract

There is an explosion of media content, especially user generated content, on the Internet. Efficient search of media data still remains a distant goal. Tagging has been used recently to bridge the "semantic gap" for images. Tagging of video data poses several challenges. The temporal nature of video requires support from the media player for video tagging. Unlike images which can be tagged simultaneously with viewing, tagging of video is typically not done at first viewing: videos are best tagged after viewing them at least once in entirety. This is not a preferred solution since the entire video has to be played again for tagging. In this paper, we propose a compact representation called "tagboard" which reduces the cognitive overload associated with video tagging. Tagboard also facilitates tag propagation. The technique is based on image similarity and dimensionality reduction. The ease of tagging improves metadata creation there by improving social search.

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cover image ACM Conferences
MM '08: Proceedings of the 16th ACM international conference on Multimedia
October 2008
1206 pages
ISBN:9781605583037
DOI:10.1145/1459359
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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Publication History

Published: 26 October 2008

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  1. video tagging

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MM08
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MM08: ACM Multimedia Conference 2008
October 26 - 31, 2008
British Columbia, Vancouver, Canada

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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