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Author:

Wang, Chengzhang (Wang, Chengzhang.) | Yin, Baocai (Yin, Baocai.) (Scholars:尹宝才) | Shi, Qin (Shi, Qin.) | Sun, Yanfeng (Sun, Yanfeng.) (Scholars:孙艳丰)

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EI Scopus

Abstract:

A novel model matching method based on improved genetic algorithm is presented in this paper to improve efficiency of matching process for 3D face synthesis. New method is independent from initial values and more robust than stochastic gradient descent method. Improved genetic algorithm has strong global searching ability. Crossover and mutation probability are regulated during optimization process to improve precision and convergence speed of the algorithm. Experimental results show our new model matching method has good performance on 3D face synthesis.

Keyword:

Gradient methods Genetic algorithms Three dimensional computer graphics Artificial intelligence Stochastic systems

Author Community:

  • [ 1 ] [Wang, Chengzhang]Beijing Municipal Multimedia and Intelligent Software Key Lab, Beijing University of Technology, Beijing 100022, China
  • [ 2 ] [Yin, Baocai]Beijing Municipal Multimedia and Intelligent Software Key Lab, Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Shi, Qin]Beijing Municipal Multimedia and Intelligent Software Key Lab, Beijing University of Technology, Beijing 100022, China
  • [ 4 ] [Sun, Yanfeng]Beijing Municipal Multimedia and Intelligent Software Key Lab, Beijing University of Technology, Beijing 100022, China

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Source :

Year: 2005

Page: 183-187

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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