• DocumentCode
    1094582
  • Title

    A Hierarchical Compositional Model for Face Representation and Sketching

  • Author

    Xu, Zijian ; Chen, Hong ; Zhu, Song-Chun ; Luo, Jiebo

  • Author_Institution
    Moody´´s Corp., San Francisco, CA
  • Volume
    30
  • Issue
    6
  • fYear
    2008
  • fDate
    6/1/2008 12:00:00 AM
  • Firstpage
    955
  • Lastpage
    969
  • Abstract
    This paper presents a hierarchical-compositional model of human faces, as a three-layer AND-OR graph to account for the structural variabilities over multiple resolutions. In the AND-OR graph, an AND-node represents a decomposition of certain graphical structure, which expands to a set of OR-nodes with associated relations; an OR-node serves as a switch variable pointing to alternative AND-nodes. Faces are then represented hierarchically: The first layer treats each face as a whole, the second layer refines the local facial parts jointly as a set of individual templates, and the third layer further divides the face into 15 zones and models detail facial features such as eye corners, marks, or wrinkles. Transitions between the layers are realized by measuring the minimum description length (MDL) given the complexity of an input face image. Diverse face representations are formed by drawing from dictionaries of global faces, parts, and skin detail features. A sketch captures the most informative part of a face in a much more concise and potentially robust representation. However, generating good facial sketches is extremely challenging because of the rich facial details and large structural variations, especially in the high-resolution images. The representing power of our generative model is demonstrated by reconstructing high-resolution face images and generating the cartoon facial sketches. Our model is useful for a wide variety of applications, including recognition, nonphotorealisitc rendering, superresolution, and low-bit rate face coding.
  • Keywords
    computer graphics; face recognition; graph theory; image representation; hierarchical compositional model; high-resolution images; human face representation; human face sketching; minimum description length; three-layer AND-OR graph; Hierarchical; Image Processing and Computer Vision; Statistical; Algorithms; Artificial Intelligence; Biometry; Computer Graphics; Computer Simulation; Face; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Models, Biological; Paintings; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2008.50
  • Filename
    4468712