• DocumentCode
    3580131
  • Title

    Salient region detection using high level feature

  • Author

    Zhong Liu ; Weihai Chen ; Xingming Wu

  • Author_Institution
    Sch. of Autom. Sci. & Electr. Eng., BeiHang Univ., Beijing, China
  • fYear
    2014
  • Firstpage
    1213
  • Lastpage
    1217
  • Abstract
    In the last few decades, selective visual attention has been extensively studied for its promising contributions to computer vision applications. Many different models have been proposed to compute visual saliency, which can be coarsely formulated as computational or psychophysical. Most existing methods are based on bottom-up mechanism, an automatic human behavior to guide gaze allocation. And low level features such as color, intensity and orientation are commonly adopted to compute saliency map. In this work, we propose a saliency computation method that integrates high-level information of object with low-level features. The result map is more suitable for most top-down tasks in the field of mobile robot requiring object information.
  • Keywords
    computer vision; feature extraction; gaze tracking; image colour analysis; automatic human behavior; color feature; computer vision applications; gaze allocation; high-level object information; intensity feature; low-level features; mobile robot; orientation feature; saliency computation method; saliency map; salient region detection; selective visual attention; top-down tasks; visual saliency; Computational modeling; Detectors; Feature extraction; Image color analysis; Image segmentation; Object detection; Visualization; HOG; features; high level cues; saliency; visual attention;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation Robotics & Vision (ICARCV), 2014 13th International Conference on
  • Type

    conf

  • DOI
    10.1109/ICARCV.2014.7064488
  • Filename
    7064488