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作者:

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

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EI Scopus

摘要:

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. © 2006 IEEE.

关键词:

Convergence of numerical methods Face recognition Genetic algorithms Mathematical models Probability Stochastic control systems Three dimensional

作者机构:

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

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年份: 2006

卷: 1

页码: 3643-3647

语种: 英文

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WoS核心集被引频次: 0

SCOPUS被引频次: 1

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