• DocumentCode
    2462718
  • Title

    Using Color Compatibility for Assessing Image Realism

  • Author

    Lalonde, Jean-François ; Efros, Alexei A.

  • Author_Institution
    Carnegie Mellon Univ., Pittsburgh
  • fYear
    2007
  • fDate
    14-21 Oct. 2007
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Why does placing an object from one photograph into another often make the colors of that object suddenly look wrong? One possibility is that humans prefer distributions of colors that are often found in nature; that is, we find pleasing these color combinations that we see often. Another possibility is that humans simply prefer colors to be consistent within an image, regardless of what they are. In this paper, we explore some of these issues by studying the color statistics of a large dataset of natural images, and by looking at differences in color distribution in realistic and unrealistic images. We apply our findings to two problems: 1) classifying composite images into realistic vs. non- realistic, and 2) recoloring image regions for realistic compositing.
  • Keywords
    image classification; image colour analysis; statistical analysis; very large databases; visual databases; color compatibility; color distribution; color statistics; composite image classification; image realism assessment; image region recoloring; large natural image dataset; realistic images; unrealistic images; Art; Color; Computer science; Geometry; Humans; Layout; Lighting; Painting; Physics; Statistical distributions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
  • Conference_Location
    Rio de Janeiro
  • ISSN
    1550-5499
  • Print_ISBN
    978-1-4244-1630-1
  • Electronic_ISBN
    1550-5499
  • Type

    conf

  • DOI
    10.1109/ICCV.2007.4409107
  • Filename
    4409107