• DocumentCode
    2954176
  • Title

    Salient objects detection in time sequenced images

  • Author

    Tian, Minghui ; Wan, Shohong ; Ji, Yan ; Yue, Lihua

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Sci. & Technol. of China, Hefei
  • fYear
    2008
  • fDate
    1-8 June 2008
  • Firstpage
    321
  • Lastpage
    326
  • Abstract
    Salient objects detection in time sequenced images has a very important role in many applications such as surveillance systems, tracking and recognition systems, scene analysis and so on. This paper presents a novel approach for salient objects detection in time sequenced images. The approach in this paper is based on a visual saliency model which is proposed for analysis in time sequenced images. The model in this paper is based on a bottom-up visual saliency model which is presented by Itti in 1998. Multi different features are introduced to describe salient objects globally in time sequenced images. And they are combined into a single saliency map. Salient objects in time sequenced images can be detected by the final saliency map. The detection algorithm is unsupervised and fast. The results of the experiments indicate that our approach is effective and very robust to noise, blur, contrast level and brightness level.
  • Keywords
    image sequences; object detection; bottom-up visual saliency model; salient objects detection; scene analysis; single saliency map; time sequenced images; Neural networks; Object detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1820-6
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2008.4633811
  • Filename
    4633811