DocumentCode :
2732279
Title :
Genetic Algorithm Based 3D Face Reconstruction
Author :
Wang, Chengzhang ; Yin, Baocai ; Shi, Qin ; Sun, Yanfeng
Author_Institution :
Multimedia & Intelligent Software Technol. Beijing, Beijing Univ. of Technol.
Volume :
1
fYear :
0
fDate :
0-0 0
Firstpage :
3643
Lastpage :
3647
Abstract :
A novel model matching method based on genetic algorithm is presented in this paper for 3D face reconstruction. Having constructed the morphable model, genetic algorithm is proposed to tackle model matching problem. Multi-lights illumination model is developed to fit for more complex conditions. New model matching method based on genetic algorithm is independent from initial values and more robust than stochastic gradient descent method. Crossover and mutation probability are regulated during optimization process to improve precision and convergence speed of the algorithm. Multi-lights illumination model improves the stability of 3D face reconstruction and ability to evaluate illumination conditions of input facial images. Experimental results show the proposed method has good performance on 3D face reconstruction
Keywords :
genetic algorithms; image matching; image morphing; image reconstruction; 3D face reconstruction; convergence speed; crossover probability; facial image; genetic algorithm; illumination condition evaluation; model matching; morphable model; multilights illumination model; mutation probability; optimization process; precision improvement; Deformable models; Educational technology; Face; Facial animation; Genetic algorithms; Genetic mutations; Image reconstruction; Laboratories; Lighting; Stochastic processes; 3D face reconstruction; genetic algorithm; illumination model; model matching;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
Type :
conf
DOI :
10.1109/WCICA.2006.1713049
Filename :
1713049
Link To Document :
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