NDLI: A novel 3D reconstruction algorithm based on hybrid immune particle swarm optimization

Content Provider	IEEE Xplore Digital Library
Author	Chen Zhi-Ming Cao Jian-Zhong Huang Jin-Qiu
Copyright Year	2010
Description	Author affiliation: Electronic Science Department, Huizhou University, Guangdong 516007, China (Chen Zhi-Ming; Cao Jian-Zhong; Huang Jin-Qiu)
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.
Starting Page	5228
Ending Page	5231
File Size	182943
Page Count	4
File Format	PDF
ISBN	9781424462636
e-ISBN	9787894631046
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Association of Aut
Subject Keyword	Surface reconstruction Shape Artificial Immune Optimization 3D Reconstruction Three dimensional displays Particle swarm optimization shape From Shading Image reconstruction Optimization Particle Swarm Optimization Convergence
Content Type	Text
Resource Type	Article

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