• DocumentCode
    3399415
  • Title

    Handling Uncertainty in Video Analysis with Spatiotemporal Visual Attention

  • Author

    Rapantzikos, Konstantinos ; Avrithis, Yannis ; Kollias, Stefanos

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Athens Nat. Tech. Univ.
  • fYear
    2005
  • fDate
    25-25 May 2005
  • Firstpage
    213
  • Lastpage
    217
  • Abstract
    In natural vision, we center our fixation on the most informative points in a scene in order to reduce our overall uncertainty about the scene and help interpret it. Even if we are looking for a specific stimulus around us, we face a great amount of uncertainty since that stimulus could be in any spatial location. Visual attention (VA) schemes have been proposed by researchers to account for the ability of the human eye to quickly fixate on informative regions. Recently, VA in images, and especially saliency-based VA, became an active research topic of the computer vision community. The proposed work provides an extension towards VA in video sequences by integrating spatiotemporal information. The potential applications include video classification, scene understanding, surveillance and segmentation
  • Keywords
    computer vision; feature extraction; image segmentation; image sequences; surveillance; video signal processing; computer vision; human eye; image segmentation; informative regions; natural vision; scene understanding; spatial location; spatiotemporal visual attention; surveillance; uncertainty handling; video analysis; video classification; video sequences; Application software; Computer vision; Face detection; Humans; Image segmentation; Layout; Spatiotemporal phenomena; Surveillance; Uncertainty; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
  • Conference_Location
    Reno, NV
  • Print_ISBN
    0-7803-9159-4
  • Type

    conf

  • DOI
    10.1109/FUZZY.2005.1452395
  • Filename
    1452395