• DocumentCode
    2476753
  • Title

    The Use of Genetic Programming for Learning 3D Craniofacial Shape Quantifications

  • Author

    Atmosukarto, Indriyati ; Shapiro, Linda G. ; Heike, Carrie

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Univ. of Washington, Seattle, WA, USA
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    2444
  • Lastpage
    2447
  • Abstract
    Craniofacial disorders commonly result in various head shape dysmorphologies. The goal of this work is to quantify the various 3D shape variations that manifest in the different facial abnormalities in individuals with a craniofacial disorder called 22q11.2 Deletion Syndrome. Genetic programming (GP) is used to learn the different 3D shape quantifications. Experimental results show that the GP method achieves a higher classification rate than those of human experts and existing computer algorithms.
  • Keywords
    face recognition; genetic algorithms; shape recognition; craniofacial disorders; facial abnormalities; genetic programming; learning 3D craniofacial shape quantifications; shape dysmorphologies; Face; Genetic programming; Histograms; Mouth; Nose; Shape; Three dimensional displays; 3D Shape quantification; genetic programming;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.598
  • Filename
    5595755