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
Link To Document :
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