• DocumentCode
    2218276
  • Title

    NewsLab: Exploratory Broadcast News Video Analysis

  • Author

    Ghoniem, Mohammad ; Luo, Dongning ; Yang, Jing ; Ribarsky, William

  • Author_Institution
    UNC Charlotte, Charlotte
  • fYear
    2007
  • fDate
    Oct. 30 2007-Nov. 1 2007
  • Firstpage
    123
  • Lastpage
    130
  • Abstract
    In this paper, we introduce NewsLab, an exploratory visualization approach for the analysis of large scale broadcast news video collections containing many thousands of news stories over extended periods of time. A river metaphor is used to depict the thematic changes of the news over time. An interactive lens metaphor allows the playback of fine-grained video segments selected through the river overview. Multi-resolution navigation is supported via a hierarchical time structure as well as a hierarchical theme structure. Themes can be explored hierarchically according to their thematic structure, or in an unstructured fashion using various ranking criteria. A rich set of interactions such as filtering, drill-down/roll-up navigation, history animation, and keyword based search are also provided. Our case studies show how this set of tools can be used to find emerging topics in the news, compare different broadcasters, or mine the news for topics of interest.
  • Keywords
    image resolution; image segmentation; video signal processing; NewsLab; drill-down roll-up navigation; exploratory broadcast news video analysis; exploratory visualization approach; filtering; fine-grained video segments; hierarchical theme structure; hierarchical time structure; history animation; interactive lens metaphor; keyword based search; multiresolution navigation; video collections; Animation; Broadcasting; Filtering; History; Large-scale systems; Lenses; Multimedia communication; Navigation; Rivers; Visualization; Large data exploration; animation; broadcast video analysis; clustering; comparative analysis; time filtering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Analytics Science and Technology, 2007. VAST 2007. IEEE Symposium on
  • Conference_Location
    Sacramento, CA
  • Print_ISBN
    978-1-4244-1659-2
  • Type

    conf

  • DOI
    10.1109/VAST.2007.4389005
  • Filename
    4389005