• DocumentCode
    3409660
  • Title

    Object-to-object color transfer: Optimal flows and SMSP transformations

  • Author

    Freedman, Daniel ; Kisilev, Pavel

  • Author_Institution
    Hewlett-Packard Labs., Haifa, Israel
  • fYear
    2010
  • fDate
    13-18 June 2010
  • Firstpage
    287
  • Lastpage
    294
  • Abstract
    Given a source object and a target object, we consider the problem of transferring the “color scheme” of the source to the target, while at the same time maintaining the target´s original look and feel. This is a challenging problem due to the fact that the source and target may each consist of multiple colors, each of which comes in multiple shades. We propose a two stage solution to this problem. (1) A discrete color flow is computed from the target histogram to the source histogram; this flow is computed as the solution to a convex optimization problem, whose global optimum may be found. (2) The discrete flow is turned into a continuous color transformation, which can be written as a convex sum of Stretch-Minimizing Structure-Preserving (SMSP) transformations. These SMSP transformations, which are computed based on the color flow, are affine transformations with desirable theoretical properties. The effectiveness of this two stage algorithm is validated in a series of experiments.
  • Keywords
    affine transforms; convex programming; image colour analysis; SMSP transformations; affine transformations; continuous color transformation; convex optimization problem; discrete color flow; object-to-object color transfer; source histogram; source object; stretch-minimizing structure-preserving transformations; target histogram; target object; Color; Euclidean distance; Histograms; Image segmentation; Laboratories; Machinery; Pixel; Probability distribution; Quantization; Transportation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1063-6919
  • Print_ISBN
    978-1-4244-6984-0
  • Type

    conf

  • DOI
    10.1109/CVPR.2010.5540201
  • Filename
    5540201