• DocumentCode
    1631637
  • Title

    An auto-selection method for saliency detection and its application to segment the object

  • Author

    Dang, Xuyong ; Pan, Wei

  • Author_Institution
    Dept. of Cognitive Sci., Xiamen Univ., Xiamen, China
  • Volume
    1
  • fYear
    2012
  • Firstpage
    256
  • Lastpage
    260
  • Abstract
    Based on the analysis to the three methods of IG, GBVS and PQFT, and on the comparison of their advantages and disadvantages, an auto-selection method for saliency detection is proposed by calculating the consistency between two methods. The salient object in the image is separated through combining GrabCut algorithm with the saliency map generated. The results of experiments demonstrate that our method is not only has a good performance on saliency detection but also can effectively separate the salient object.
  • Keywords
    graph theory; image segmentation; object detection; GBVS; GrabCut algorithm; IG; PQFT; autoselection method; object segmentation; saliency detection; saliency map; Computational modeling; Feature extraction; Humans; Image color analysis; Image segmentation; Vectors; Visualization; object segmention; saliency detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4673-2465-6
  • Type

    conf

  • DOI
    10.1109/MSNA.2012.6324562
  • Filename
    6324562