• DocumentCode
    3630713
  • Title

    Image Content Extraction Using a Bottom-Up Visual Attention Model

  • Author

    Ionut Pirnog;Cristina Oprea;Constantin Paleologu

  • Author_Institution
    Telecommun. Dept., Univ. Politeh. of Bucharest, Bucharest
  • fYear
    2009
  • Firstpage
    300
  • Lastpage
    303
  • Abstract
    In this paper we propose a perceptual approach to content analysis based on region segmentation. Content adaptation has become one of the most important problems in recent years due to fast growing of multimedia based services. The process of content analysis and extraction represents one step in solving the problem of content adaptation. Adaptation means the preparation and delivery of content that matches the resources of the connected terminal or network in an optimal way. The proposed content extraction method it can be classified as perceptual because it uses HVS to detect salient regions in images. The main idea of this approach is to adapt the content to the user resources without loss of salient information. Region segmentation is used for object detection and combined with the bottom-up visual attention model can lead to salient object detection.
  • Keywords
    "Image segmentation","Pixel","Data mining","Object detection","Color","Humans","Visual system","Layout","Image analysis","MPEG standards"
  • Publisher
    ieee
  • Conference_Titel
    Digital Society, 2009. ICDS ´09. Third International Conference on
  • Print_ISBN
    978-1-4244-3550-6
  • Type

    conf

  • DOI
    10.1109/ICDS.2009.32
  • Filename
    4782892