• DocumentCode
    3494930
  • Title

    Incremental sparse saliency detection

  • Author

    Li, Yin ; Zhou, Yue ; Xu, Lei ; Yang, Xiaochao ; Yang, Jie

  • Author_Institution
    Inst. of Image Process. & Pattern Recognition, Shanghai Jiaotong Univ., Shanghai, China
  • fYear
    2009
  • fDate
    7-10 Nov. 2009
  • Firstpage
    3093
  • Lastpage
    3096
  • Abstract
    By the guidance of attention, human visual system is able to locate objects of interest in complex scene. We propose a new visual saliency detection model for both image and video. Inspired by biological vision, saliency is defined locally. Lossy compression is adopted, where the saliency of a location is measured by the Incremental Coding Length(ICL). The ICL is computed by presenting the center patch as the sparsest linear representation of its surroundings. The final saliency map is generated by accumulating the coding length. The model is tested on both images and videos. The results indicate a reliable and robust saliency of our method.
  • Keywords
    computer vision; feature extraction; image representation; object detection; video coding; biological vision; human visual system; incremental coding length; lossy compression; object detection; saliency map; sparse saliency detection; sparsest linear representation; Biological system modeling; Biology computing; Humans; Image coding; Layout; Length measurement; Loss measurement; Testing; Video compression; Visual system; Incremental Coding length; Saliency Detection; Sparse Coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2009 16th IEEE International Conference on
  • Conference_Location
    Cairo
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4244-5653-6
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2009.5414465
  • Filename
    5414465