DocumentCode :
2076250
Title :
A novel 3D reconstruction algorithm based on hybrid immune particle swarm optimization
Author :
Chen Zhi-ming ; Cao Jian-zhong ; Huang Jin-Qiu
Author_Institution :
Electron. Sci. Dept., Huizhou Univ., Huizhou, China
fYear :
2010
fDate :
29-31 July 2010
Firstpage :
5228
Lastpage :
5231
Abstract :
Shape from shading (SFS) is an important method for such fields as surface measurement of an object. In order to improve the SFS 3D reconstruction accuracy, utilizing the fact that artificial immune optimization and particle swarm optimization algorithms can compensate for each other, a reconstruction method based on a hybrid immune particle swarm optimization algorithm is proposed in this paper. The design and implementation of this hybrid algorithm is discussed in detail. A synthetic vase and a scene image are used to test the validation of the proposed method, and a comparison is made. Experiment results show that the proposed method can achieve higher accuracy and is also faster.
Keywords :
computer vision; image reconstruction; particle swarm optimisation; 3D reconstruction algorithm; hybrid immune particle swarm optimization; shape from shading; surface measurement; Convergence; Image reconstruction; Optimization; Particle swarm optimization; Shape; Surface reconstruction; Three dimensional displays; 3D Reconstruction; Artificial Immune Optimization; Particle Swarm Optimization; shape From Shading;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
Type :
conf
Filename :
5572241
Link To Document :
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