skip to main content
10.1145/1282280.1282379acmconferencesArticle/Chapter ViewAbstractPublication PagescivrConference Proceedingsconference-collections
Article

Video retrieval with multi-modal features

Published: 09 July 2007 Publication History

Abstract

In the paper, our video retrieval system is presented. The system acts as a decision support system to help users to find what they want with many analysis and visualization tools provided by the system. It consists of three basic retrieval models which searches shots in text, image and concept space respectively. The results from different modalities are fused to achieve better performance. The relevance shots are shown to users in different threads and expanded in different ways to help users try their best to make correct decision during the retrieval procedure.

References

[1]
Cao, J., Lan, Y., Li, J. et al. Intelligent Multimedia Group of Tsinghua University at TRECVID 2006. TREC Video Retrieval Evaluation Online Proceedings, 2006.
[2]
http://www.lemurproject.org/
[3]
Liu, X., Wang D., Li, J., and Zhang B. The Feature and Spatial Covariant Kernel: Adding Implicit Spatial Constraints to Histogram. To appear in ACM International Conference on Image and Video Retrieval (CIVR 2007).
[4]
Li, X., Wang D., Li, J., and Zhang B. Video Search in Concept Subspace: A Text-Like Paradigm. To appear in ACM International Conference on Image and Video Retrieval (CIVR 2007).

Cited By

View all
  • (2010)From Biomedical Image Analysis to Biomedical Image Understanding Using Machine LearningBiomedical Image Analysis and Machine Learning Technologies10.4018/978-1-60566-956-4.ch001(1-26)Online publication date: 2010

Index Terms

  1. Video retrieval with multi-modal features

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    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]

    Sponsors

    In-Cooperation

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 09 July 2007

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. concept based search
    2. multi-modal fusion

    Qualifiers

    • Article

    Conference

    CIVR07
    Sponsor:

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 07 Mar 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2010)From Biomedical Image Analysis to Biomedical Image Understanding Using Machine LearningBiomedical Image Analysis and Machine Learning Technologies10.4018/978-1-60566-956-4.ch001(1-26)Online publication date: 2010

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media