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Supporting semantic visual feature browsing in contentbased video retrieval

Published: 06 August 2006 Publication History

Abstract

A new shot level video retrieval system that supports semantic visual features (e.g., car, mountain, and fire) browsing is developed to facilitate content-based retrieval. The video's binary semantic feature vector is utilized to calculate the score of similarity between two shot keyframes. The score is then used to browse the "similar" keyframes in terms of semantic visual features.

References

[1]
Heesch, D., Howarth, P., Magalhaes, J., May, A., Pickering, M., Yavlinsky, A., and ruger, S. (2004). Video retrieval using search and browsing. In proceedings of TRECVID2004.
[2]
Wildemuth, M. B., Yang, M., Hughes, A., Gruss, R., Geisler, G., and Marchionini, G. (2003). Access via features versus access via transcripts: user performance and satisfaction. In proceedings of TRECVID2003.

Cited By

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  • (2012)Temporal-Based Video Event Detection and RetrievalInternational Journal of Organizational and Collective Intelligence10.4018/ijoci.20121001033:4(39-51)Online publication date: Oct-2012
  • (2011)Temporal-Based Video Event Detection and RetrievalMachine Learning Techniques for Adaptive Multimedia Retrieval10.4018/978-1-61692-859-9.ch010(214-227)Online publication date: 2011

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  1. Supporting semantic visual feature browsing in contentbased video retrieval

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    cover image ACM Conferences
    SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
    August 2006
    768 pages
    ISBN:1595933697
    DOI:10.1145/1148170
    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: 06 August 2006

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    Author Tags

    1. content-based
    2. user interface
    3. video browsing
    4. video retrieval

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    SIGIR06
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    SIGIR06: The 29th Annual International SIGIR Conference
    August 6 - 11, 2006
    Washington, Seattle, USA

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    Overall Acceptance Rate 792 of 3,983 submissions, 20%

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    Cited By

    View all
    • (2012)Temporal-Based Video Event Detection and RetrievalInternational Journal of Organizational and Collective Intelligence10.4018/ijoci.20121001033:4(39-51)Online publication date: Oct-2012
    • (2011)Temporal-Based Video Event Detection and RetrievalMachine Learning Techniques for Adaptive Multimedia Retrieval10.4018/978-1-61692-859-9.ch010(214-227)Online publication date: 2011

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