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Video search by multi-modal and clustering analysis

Published: 09 July 2007 Publication History

Abstract

We introduce a video search system using multi-modal and clustering analysis. In this system, users can make queries by keywords or by visual contents such as frames or rectangle regions within a frame, the retrieved results are then organized into clusters and only representative frames of these clusters are shown to users. Experiments on TRECVID datasets showed promising results.

Reference

[1]
J. Sivic and A. Zisserman. Video google: A text retrieval approach to object matching in videos. In Proc. Intl. Conf. on Computer Vision (ICCV), volume 2, pages 1470--1477, 2003.

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  • (2010)Multi modal semantic indexing for image retrievalProceedings of the ACM International Conference on Image and Video Retrieval10.1145/1816041.1816091(342-349)Online publication date: 5-Jul-2010

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cover image ACM Conferences
CIVR '07: Proceedings of the 6th ACM international conference on Image and video retrieval
July 2007
655 pages
ISBN:9781595937339
DOI:10.1145/1282280
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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New York, NY, United States

Publication History

Published: 09 July 2007

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Author Tags

  1. RSC clustering
  2. SIFT feature
  3. multi-modal video search

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  • (2010)Multi modal semantic indexing for image retrievalProceedings of the ACM International Conference on Image and Video Retrieval10.1145/1816041.1816091(342-349)Online publication date: 5-Jul-2010

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