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Author:

Wang, CZ (Wang, CZ.) | Yin, BC (Yin, BC.) (Scholars:尹宝才) | Shi, Q (Shi, Q.) | Sun, YF (Sun, YF.) (Scholars:孙艳丰)

Indexed by:

CPCI-S

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:

3D face synthesis Genetic Algorithm morphable model

Author Community:

  • [ 1 ] Beijing Univ Technol, Beijing Municipal Multimedia & Intelligent Softwa, Beijing 100022, Peoples R China

Reprint Author's Address:

  • [Wang, CZ]Beijing Univ Technol, Beijing Municipal Multimedia & Intelligent Softwa, Beijing 100022, Peoples R China

Email:

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Source :

ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS II

ISSN: 1571-5736

Year: 2005

Volume: 187

Page: 183-187

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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