• DocumentCode
    3049327
  • Title

    Extracting regions of interest based on visual attention model

  • Author

    Lin, Qing ; Xu, Xiaogang ; Zhan, Yongzhao ; Liao, Dingan

  • Author_Institution
    Sch. of Comput. Sci. & Telecommun. Eng., Jiangsu Univ., Zhenjiang, China
  • fYear
    2011
  • fDate
    26-28 July 2011
  • Firstpage
    313
  • Lastpage
    316
  • Abstract
    This paper proposed a new approach of extracting regions of interest based on visual attention model, which segmented image regions with the region growing algorithm. According to the physiological characteristics of Human Visual System (HVS), image features were extracted by non-uniform sampling of image and computing "center-surround", which were used to simulate the human visual receptive field properties. Features became multi-scale conspicuity maps, which were combined into a saliency map. The focus of attention (FOA) as seeds of the region growing algorithm was obtained by the "winner-take-all" (WTA) competition. Then the regions of interest were extracted by using the region growing algorithm. The experiment results show that this approach can select suitable seeds automatically and the extraction of regions of interest can be consistent with human visual attention mechanism.
  • Keywords
    feature extraction; image sampling; image segmentation; FOA; WTA competition; focus of attention; human visual receptive field properties; human visual system; image feature extraction; image segmentation; multiscale conspicuity maps; nonuniform image sampling; region growing algorithm; regions of interest extraction; saliency map; visual attention model; winner-take-all competition; Feature extraction; Humans; Image color analysis; Image retrieval; Image segmentation; Semantics; Visualization; focus of attention; region growing; regions of interest; visual attention model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Technology (ICMT), 2011 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-61284-771-9
  • Type

    conf

  • DOI
    10.1109/ICMT.2011.6003038
  • Filename
    6003038