A Synergistic Approach to Efficient Interactive Video Retrieval

  • Andreas Girgensohn
  • John Adcock
  • Matthew Cooper
  • Lynn Wilcox
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3585)


A video database can contain a large number of videos ranging from several minutes to several hours in length. Typically, it is not sufficient to search just for relevant videos, because the task still remains to find the relevant clip, typically less than one minute of length, within the video. This makes it impor tant to direct the users attention to the most promising material and to indicate what material they already investigated. Based on this premise, we created a video search system with a powerful and flexible user interface that incorporates dynamic visualizations of the underlying multimedia objects. The system employes an automatic story segmentation, combines text and visual search, and displays search results in ranked sets of story keyframe collages. By adapting the keyframe collages based on query relevance and indicating which portions of the video have already been explored, we enable users to quickly find relevant sec tions. We tested our system as part of the NIST TRECVID interactive search evaluation, and found that our user interface enabled users to find more relevant results within the allotted time than other systems employing more sophisticated analysis techniques but less helpful user interfaces.


Query Term Mean Average Precision Video Retrieval Video Shot Text Search 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© IFIP International Federation for Information Processing 2005

Authors and Affiliations

  • Andreas Girgensohn
    • 1
  • John Adcock
    • 1
  • Matthew Cooper
    • 1
  • Lynn Wilcox
    • 1
  1. 1.FX Palo Alto LaboratoryPalo AltoUSA

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