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.
Chapter PDF
Similar content being viewed by others
References
Parke F. I. A Parametric Model of Human Faces. PhD thesis, Salt Lake City: University of Utah, 1974.
Pighin F, Hecker J, et al. Synthesizing realistic facial expressions from photographs. In Proceedings of SIGGRAPH’98, Orlando, Florida: ACM Press, 1998: 75–84.
Lee W S, Thalmann N M. Fast Head Modeling for Animation. Journal Image and Vision Computing, 2000, 18(4): 355–364.
Blanz V, Vetter T. A morphable model for the synthesis of 3D faces. In Proceeding of SIGGRAPH’99, Los Angeles: ACM Press, 1999: 187–194.
Fletcher, R., Practical Methods of Optimization, Vol. 1: Unconstrained Optimization, John Willy and Sons, Chichester, 1980.
Cyberware Laboratory Inc, http://www.cyberware.com
Ozcan E., Onbasioglu E., Genetic algorithms for parallel code optimization. Congress on Evolutionary Computation, 19–23 June, 2004, 2(2): 1375–1381.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 International Federation for Information Processing
About this paper
Cite this paper
Wang, C., Yin, B., Shi, Q., Sun, Y. (2005). An Improved 3D Face Synthesis Based on Morphable Model. In: Li, D., Wang, B. (eds) Artificial Intelligence Applications and Innovations. AIAI 2005. IFIP — The International Federation for Information Processing, vol 187. Springer, Boston, MA. https://doi.org/10.1007/0-387-29295-0_19
Download citation
DOI: https://doi.org/10.1007/0-387-29295-0_19
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-28318-0
Online ISBN: 978-0-387-29295-3
eBook Packages: Computer ScienceComputer Science (R0)