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Connect commercial films with realities

Published: 16 April 2013 Publication History

Abstract

Broadcast TV program is a quite informative media resource which records our daily life over the time. While for emphasizing real-time reporting, those out-of-date video archives once were elaborately created with high quality are always left without being fully used. In this paper, many known state-of-the-art retrieval technologies are integrated into a commercial film retrieval system, which manages to index a huge commercial dataset archived from five TV channels within recent three years. The final purpose is to connect images queried by users with our archived broadcast video dataset via searching relevant commercials and accessing their broadcast information, such as air time and replay frequency. This system also serves as one part of our ongoing broadcast TV program reusing project.

References

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R. Arandjelovic and A. Zisserman. Three things everyone should know to improve object retrieval. CVPR, 2012.
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O. Chum, J. Matas, and J. Kittler, Locally Optimized RANSAC. DAGM-Symposium. 2003.
[3]
C.-Z. Zhu and S. Satoh. Large vocabulary quantization for searching instances from videos. ICMR, 2012.
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X. Wu and S. Satoh, Commercial mining based on temporal recurrence hashing algorithm and bag-of-fingerprints model. ICIP, 2011.
[5]
D. Le, C.-Z. Zhu, S. Poullot, et al. National Institute of Informatics, Japan at TRECVID 2011. TRECVID, 2011.

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cover image ACM Conferences
ICMR '13: Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
April 2013
362 pages
ISBN:9781450320337
DOI:10.1145/2461466
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2013

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Author Tags

  1. broadcast video indexing
  2. commercial films
  3. video search

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  • Demonstration

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ICMR'13
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Acceptance Rates

ICMR '13 Paper Acceptance Rate 38 of 96 submissions, 40%;
Overall Acceptance Rate 254 of 830 submissions, 31%

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