• DocumentCode
    671067
  • Title

    Detection of salient objects in computer synthesized images based on object-level contrast

  • Author

    Lu Dong ; Weisi Lin ; Yuming Fang ; Shiqian Wu ; Hock Soon Seah

  • Author_Institution
    Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2013
  • fDate
    17-20 Nov. 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this work, we propose a method to detect visually salient objects in computer synthesized images from 3D meshes. Different from existing detection methods on graphic saliency which compute saliency based on pixel-level contrast, the proposed method computes saliency by measuring object-level contrast of each object to the other objects in a rendered image. Given a synthesized image, the proposed method first extracts dominant colors from each object, and represents each object with the dominant color descriptor (DCD). Saliency is measured as the contrast between the DCD of the object and the DCDs of its surrounding objects. We evaluate the proposed method on a data set of computer rendered images, and the results show that the proposed method obtains much better performance compared with existing related methods.
  • Keywords
    feature extraction; image colour analysis; object detection; rendering (computer graphics); 3D mesh; DCD; computer-rendered images; computer-synthesized images; dominant color descriptor; dominant color extraction; graphic saliency; object-level contrast; pixel-level contrast; surrounding objects; visual salient object detection method; Computers; Feature extraction; Graphics; Image color analysis; Painting; Solid modeling; Three-dimensional displays; computer synthesized images; object-level contrast; saliency detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Visual Communications and Image Processing (VCIP), 2013
  • Conference_Location
    Kuching
  • Print_ISBN
    978-1-4799-0288-0
  • Type

    conf

  • DOI
    10.1109/VCIP.2013.6706362
  • Filename
    6706362