• DocumentCode
    3017990
  • Title

    Saliency Detection: A Spectral Residual Approach

  • Author

    Hou, Xiaodi ; Zhang, Liqing

  • Author_Institution
    Shanghai Jiao Tong Univ., Shanghai
  • fYear
    2007
  • fDate
    17-22 June 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    The ability of human visual system to detect visual saliency is extraordinarily fast and reliable. However, computational modeling of this basic intelligent behavior still remains a challenge. This paper presents a simple method for the visual saliency detection. Our model is independent of features, categories, or other forms of prior knowledge of the objects. By analyzing the log-spectrum of an input image, we extract the spectral residual of an image in spectral domain, and propose a fast method to construct the corresponding saliency map in spatial domain. We test this model on both natural pictures and artificial images such as psychological patterns. The result indicate fast and robust saliency detection of our method.
  • Keywords
    feature extraction; object detection; artificial images; features independent; image log-spectrum; intelligent behavior; psychological patterns; saliency detection; spatial domain; spectral domain; spectral residual approach; Computational modeling; Humans; Image analysis; Image coding; Machine vision; Object detection; Object recognition; Redundancy; Statistical distributions; Visual system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
  • Conference_Location
    Minneapolis, MN
  • ISSN
    1063-6919
  • Print_ISBN
    1-4244-1179-3
  • Electronic_ISBN
    1063-6919
  • Type

    conf

  • DOI
    10.1109/CVPR.2007.383267
  • Filename
    4270292