• DocumentCode
    3093310
  • Title

    Vision-Related MLS Image Deformation Using Saliency Map

  • Author

    Zhang, Yong ; Lai, Jianhuang ; Du, Xiaorong

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Sun Yat-Sen Univ., Guangzhou, China
  • fYear
    2011
  • fDate
    12-15 Aug. 2011
  • Firstpage
    193
  • Lastpage
    198
  • Abstract
    We provide a vision-related image deformation method based on Moving Least Squares (MLS) and visual saliency map. As the improvement of image deformation using MLS, we propose a new weight function to improve the MLS image deformation. A visual saliency-related deformation weight definition is proposed to ensure deformations are more easily to kept local shape on high visual saliency region and changed the non-vital part of image. Being different from the original MLS method, our weight function not only based on the distance between current pixel and a certain control points but also has benefited from the visual saliency map of undeformed image. In order to adjust the saliency of salient region during deformation, we have revised original visual saliency map by 2 parameters: segmentation threshold and gray level increment. All experiments and analysis have shown that our deformation can achieve a more realistic effect than original MLS image deformation.
  • Keywords
    computer vision; image segmentation; least squares approximations; gray level increment; moving least squares method; segmentation threshold; vision-related MLS image deformation; visual saliency map; visual saliency region; Equations; Image segmentation; Interpolation; Mathematical model; Shape; Spline; Visualization; MLS; image deformation; saliency map; vision-related deformation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Graphics (ICIG), 2011 Sixth International Conference on
  • Conference_Location
    Hefei, Anhui
  • Print_ISBN
    978-1-4577-1560-0
  • Electronic_ISBN
    978-0-7695-4541-7
  • Type

    conf

  • DOI
    10.1109/ICIG.2011.173
  • Filename
    6005553